CausalCare: Propelling health forward

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musondabemba
Project Owner

CausalCare: Propelling health forward

Funding Requested

$120,000 USD

Expert Review
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Overview

The project aims to develop a comprehensive healthcare scheduling system that optimizes various aspects of healthcare operations. It encompasses capacity planning, nurse scheduling, patient appointments, operating theatre planning, bed management, queuing networks, medical supply logistics, home health care, and healthcare planning and control.

Proposal Description

Company Name (if applicable)

HealthCausal Innovations.

How our project will contribute to the growth of the decentralized AI platform

This project is dedicated to improving the efficiency of health care by improving the scheduling of health care resources (such as doctors, nurses, & medical equipment) to meet patient needs. Building from operations research & industrial engineering, we address the complexities of healthcare scheduling in contexts ranging from ambulatory clinics to out-patient procedure centers to surgical theaters. All of them demonstrate the importance of applying resources in accordance to anticipated needs.

The core problem we are aiming to solve

The healthcare scheduling system optimizes operations to enhance efficiency, care quality, and patient outcomes. It tackles challenges in resource management, such as staffing and facility allocation, to ensure timely and high-quality care. By leveraging advanced algorithms and predictive analytics, the system automates scheduling tasks, adjusts in real-time, and provides decision support tools for administrators. This will empower healthcare providers to optimize care delivery, resource allocation, and operational efficiency, ultimately improving patient care and outcomes.

Our specific solution to this problem

HealthCausal Innovations plans to use advanced algorithms to analyze healthcare data comprehensively. This will involve data collection, feature extraction, and training a causality detection AI model. This model will be integrated into the scheduling algorithm to adjust decisions dynamically based on predicted causal effects. Continuous learning and decision support tools will be provided, while adhering to validation standards and regulatory requirements. This approach aims to improve diagnostic accuracy, patient outcomes, and operational efficiency in healthcare.

Project details

The project aims to develop a comprehensive healthcare scheduling system encompassing various aspects of healthcare operations, including capacity planning, nurse scheduling, patient appointments, operating theatre planning, bed management, queuing networks, medical supply logistics, home health care, and healthcare planning and control. 

1. Capacity Planning: This approach delves into the intricacies of capacity planning in healthcare settings, emphasizing the need for surplus capacity to accommodate fluctuations in demand. It explores queuing models to calculate the required level of surplus capacity and discusses strategies for pooling resources to optimize capacity utilization.
2. Nurse Scheduling: Focusing on optimizing nurse schedules for both ward and operating room settings, presenting mathematical programming formulations. It discusses how scheduling models can incorporate multiple objectives, such as cost and shift preferences, to create efficient and effective nurse schedules.
3. Patient Appointments in Ambulatory Care: Describing systems for setting outpatient appointments, outlining a two-stage process involving clinic profiling and patient booking. It explores methods for efficiently allocating appointment slots and managing patient appointments to optimize clinic operations.
4. Operating Theatre Planning and Scheduling: This approach addresses the crucial role of operating theatres in hospital activity. It develops planning models for scheduling elective procedures within a hierarchical structure, aiming to maximize operating theatre utilization and minimize scheduling conflicts.
5. Appointment Planning and Scheduling in Outpatient Procedure Centers: Focusing on specialized procedure facilities such as outpatient surgery centers, providing systems for setting appointments for less complex cases. It discusses strategies for efficient appointment scheduling to streamline operations and improve patient satisfaction.
6. Human and Artificial Scheduling System for Operating Rooms: Centered on scheduling surgical cases within operating rooms, we emphasize the integration of human schedulers’ knowledge into scheduling systems. It addresses challenges such as delays and cancellations while striving to optimize operating room utilization and minimize schedule deviations.
7. Bed Management and Control: Examining the pivotal role of inpatient beds in hospital operations, here we explore bed management strategies to optimize patient flow. It discusses the relationship between bed management, intake, and discharge processes, aiming to enhance hospital efficiency and patient throughput.
8. Queuing Networks in Healthcare Systems: We provide an analytical framework for modeling queueing networks within complex healthcare systems. It identifies bottlenecks and inefficiencies in patient flow and proposes strategies to improve system performance and patient satisfaction.
9. Medical Supply Logistics: Addressing the scheduling and management of medical supplies, focusing on coordinating supply flow with patient demand. It uses the management of blood supply as a case study to illustrate effective supply logistics strategies and inventory management techniques.
10. Operations Research Applications in Home Health Care: Here we present models for managing the movement and timing of healthcare professionals providing home-based care. It discusses resource allocation and scheduling strategies to optimize home health care services and meet patient needs effectively.
11. A Framework for Healthcare Planning and Control: This approach proposes an integrative framework for healthcare system scheduling. It outlines four management areas (medical planning, resource allocation, capacity planning, financial planning) implemented within a four-level hierarchy (strategic, offline operational, online operational, and tactical) providing a comprehensive approach to healthcare scheduling and management.
Overall, the project aims to provide valuable insights and practical solutions for optimizing healthcare operations, enhancing patient care, and improving overall healthcare system performance.

The competition and our USPs

No

Our team

  1. Musonda Bemba: Project Owner.
  2. Lemi Debele: Machine learning Engineer. 
    With hands on experience in Machine learning and Deep Learning.
  3. [         ]: Data Scientist needed.
View Team

What we still need besides budget?

Yes

Describe the resources you still need

Additional expertise from fellow AI developers and expert Data Scientist.

Existing resources we will leverage for this project

No

Open Source Licensing

none

AI services (New or Existing)

Causality Detection.

How it will be used

Integrating causality detection AI into our healthcare scheduling system will enhance efficiency by revealing relationships between scheduling decisions and outcomes. This technology analyzes historical data to identify patterns and causal links empowering providers to optimize resource allocation and improve patient care delivery. By understanding how scheduling decisions impact metrics like patient wait times and staff utilization providers can optimize future decisions to enhance efficiency

Proposal Video

Placeholder for Spotlight Day Pitch-presentations. Video's will be added by the DF team when available.

  • Total Milestones

    4

  • Total Budget

    $120,000 USD

  • Last Updated

    20 May 2024

Milestone 1 - API Calls & Hostings

Description

This milestone represents the required reservation of 25% of your total requested budget for API calls or hosting costs. Because it is required we have prefilled it for you and it cannot be removed or adapted.

Deliverables

You can use this amount for payment of API calls on our platform. Use it to call other services or use it as a marketing instrument to have other parties try out your service. Alternatively you can use it to pay for hosting and computing costs.

Budget

$30,000 USD

Milestone 2 - Data Acquisition

Description

This integrated healthcare scheduling data acquisition strategy aims at allocating funds to optimize resource utilization while ensuring compliance and data integrity. This will involve investing in capacity planning models to manage fluctuations in patient demand and pooling resources efficiently. Nurse scheduling formulations consider cost and shift preferences ensuring optimal allocation across wards and operating rooms. Patient appointment systems in ambulatory care are optimized dividing days into slots and streamlining booking processes. Operating theatre planning aims at utilizing hierarchical structures for elective procedures maximizing theatre resource utilization. Human and artificial scheduling systems will incorporate expert knowledge to minimize disruptions and delays. Bed management controls will facilitate efficient patient flow through the hospital. Queuing network analysis identifies and addresses bottlenecks optimizing patient flow. Medical supply logistics are managed to meet patient demands while minimizing waste. Operations research in home healthcare ensures efficient resource allocation for patient care. This integrated approach within a hierarchical management framework ensures effective healthcare scheduling while facilitating access to relevant datasets for improved decision-making.

Deliverables

We prioritize patient confidentiality and data security adhering strictly to regulations such as the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR). Throughout the process strict measures are implemented to safeguard sensitive patient information ensuring compliance with these regulations. By incorporating robust encryption protocols access controls and secure data storage solutions patient data remains protected at every stage of acquisition and utilization. This commitment to maintaining privacy & security not only fosters trust among patients but also upholds the ethical standards expected in healthcare operations.

Budget

$20,000 USD

Milestone 3 - Algorithm Development & Optimization

Description

This milestone involves designing and refining algorithms to enhance the efficiency & effectiveness of scheduling processes in healthcare settings. This will include developing innovative algorithms tailored to specific scheduling challenges such as nurse scheduling patient appointments operating theatre planning and bed management. Optimization techniques are employed to improve resource allocation minimize wait times and maximize the utilization of healthcare resources. Throughout the process a focus is maintained on incorporating feedback from investors leveraging data-driven insights and adhering to regulatory requirements to ensure that the developed algorithms meet the evolving needs of healthcare organizations while delivering high-quality care to patients.

Deliverables

Our team will encompass the creation of advanced algorithms tailored to specific scheduling challenges within healthcare settings. Through rigorous optimization techniques these algorithms aim to enhance resource allocation minimize wait times and maximize the utilization of healthcare resources. Leveraging community feedback and data-driven insights the developed algorithms are designed to meet regulatory requirements such as HIPAA and GDPR while delivering efficient and effective scheduling solutions. This deliverable represents a significant advancement in healthcare scheduling technology promising to streamline operations improve patient experiences and ultimately contribute to better healthcare outcomes.

Budget

$50,000 USD

Milestone 4 - Prototype development & testing

Description

This milestone focuses on creating and refining prototypes of the scheduling algorithms and systems designed in the previous stage. These prototypes are subjected to rigorous testing in simulated & real-world healthcare environments to assess their functionality efficiency and usability. Feedback from healthcare professionals investors and the SNET AI community will be gathered and incorporated iteratively to refine the prototypes further. The testing process will ensure that the scheduling systems meet the specific needs of healthcare settings adhering to regulatory requirements & delivering tangible improvements in resource allocation patient flow and overall healthcare delivery.

Deliverables

Our team will focus on the creation and refinement of functional prototypes based on advanced scheduling algorithms. These prototypes will have to undergo comprehensive testing in both simulated and real healthcare environments to evaluate their effectiveness efficiency and usability. Iterative feedback from healthcare professionals investors and the SNET AI community that will help guide the refinement process ensuring that our prototypes meet the specific requirements of healthcare settings and comply with regulatory standards such as HIPAA and GDPR. We represent a validated solution that promises to optimize resource allocation streamline scheduling processes and enhance overall healthcare delivery ultimately leading to improved patient outcomes and experiences.

Budget

$20,000 USD

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Reviews & Rating

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9 ratings
  • 0
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    Victor2815
    May 12, 2024 | 3:59 PM

    Overall

    5

    • Feasibility 4
    • Viability 5
    • Desirabilty 5
    • Usefulness 5
    THE PROJECT IS POTENTIAL BUT NOT REALLY PERFECT

    Your project has a very good meaning towards the community, it brings good and noble benefits. This project is published from the desire for development and health care. However, in the current market, I've found quite a few projects that have similar goals to the one the topic group proposed, and to be honest I haven't really found many goals that are different from other projects out there in the market. A lot of people are moving towards healthcare using advanced algorithms and AI models I don't find anything special in your publishing project The most important thing for with a competitive field like this - being unique, this will attract and bring more users so your project can develop better. But I think you have also invested a lot of effort I put all my effort and enthusiasm into this project proposal, so I hope that one day your project will be successful.

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    musondabemba
    May 14, 2024 | 8:35 AM
    Project Owner

    Thank you for taking your time to review our project proposal and for your thoughtful feedback. I truly appreciate your recognition of the meaningful impact my project aims to have on the SNET AI community and its focus on healthcare development. Your insight regarding the competitive landscape and the importance of uniqueness is duly noted, and I am committed to further refining my project to distinguish it from others in the market. I assure you that I am dedicated to continuous improvement and innovation, and I am grateful for your encouragement and support on this journey towards success.

  • 0
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    Mai Pippi
    May 7, 2024 | 4:50 AM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 4
    • Usefulness 4
    THE PROJECT NEEDS CLARIFYING SOME ASPECTS

    The healthcare industry has to face challenges in managing patient care and allocating appropriate nurse and doctor resources. Therefore, the project brings a solution to create a system that applies AI in allocating medical resources to patient needs. The project also helps evaluate long-term patient effectiveness. If the project is successful, it will help save time, money, and effort for the health sector. It also helps improve patient satisfaction from examination to treatment.

    Although the project has good ideas and great expectations, I have a few concerns as follows:

    First, the group calls for a capital of 120,000 USD but does not have a detailed capital allocation table. It would be better if the team had a capital allocation table based on the amount of work, the hours worked, and the goals to be delivered.

    Second, this is a project that requires complex skills in data technology and medical science. However, the team does not have suitable personnel to undertake these tasks. That affects the work progress and feasibility of the project.

    Finally, the team also needs to pay attention to marketing factors. How to attract users and educate them to create the habit of using this service? If there are few users, evaluating the effectiveness of the project will not be objective. The team should consider the marketing category in the proposal.

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    musondabemba
    May 7, 2024 | 2:27 PM
    Project Owner

    As the project owner, I am deeply committed to bringing this initiative to fruition with utmost dedication and enthusiasm. Your feedback is invaluable, and I assure you that we will address each concern with utmost priority. A detailed capital allocation table to ensure transparency and efficiency in resource management can be provided. Moreover, we are actively seeking individuals with the necessary expertise to boost our team and propel the project forward. We understand the significance of a robust marketing strategy to attract users and ensure the project’s effectiveness. Rest assured, we are fully dedicated to exceeding the project's expectations and making a meaningful impact in the healthcare sector. Thank you for your support! 

  • 0
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    TrucTrixie
    May 6, 2024 | 11:42 AM

    Overall

    4

    • Feasibility 3
    • Viability 3
    • Desirabilty 4
    • Usefulness 4
    A good way to get more transparency

    What is a good commitment to using the budget? Can you share that right in the presentation of this proposal?

    The funding request of $120,000 is not a small number for a proposal that has gone through the rounds of DeepFunding that I have ever witnessed.

    Are you firmly committed to using capital effectively?

    Presenting your commitment is a good idea in my opinion - it's a good way to contribute to the transparency of your proposal and further strengthen your credibility.

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    musondabemba
    May 7, 2024 | 4:43 PM
    Project Owner

    Thank you for your feedback and for emphasizing the importance of transparency and accountability in our proposal. We wholeheartedly agree that it’s essential to demonstrate our commitment to using the budget effectively. Rest assured, we will firmly dedicate to maximizing the impact of every dollar invested in our project. To address your concerns and contribute to transparency, we can include a detailed breakdown of our commitment to budget utilization directly in our presentation video or in the proposal. This will showcase our dedication to responsible financial management and further boost the credibility of our proposal. We appreciate your insights and are committed to upholding the highest standards of transparency and accountability throughout the project. Thank you for your support and guidance! Don't forget to Vote! 🗳️ 

  • 0
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    Viclex Ad
    May 6, 2024 | 12:26 AM

    Overall

    4

    • Feasibility 3
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    Health Causal Innovations Proposal

    HealthCausal Innovations offers a viable healthcare scheduling optimization solution that fits both the goals of deep funding and the demands of the industry. It might make a big difference if executed with concentration and appropriate tweaks.

    Possibility: 

    The plan uses cutting-edge algorithms to maximize efficiency while displaying a thorough awareness of the challenges associated with healthcare scheduling. The ambitious scope, though, can present difficulties in practical application.


    Viability: 

    The group exhibits pertinent experience, but the absence of a data scientist could affect judgments based on data. The project's scale seems to warrant the budgetary commitment.

    Desirability: 

    The project is in line with market demands and addresses important issues related to the optimization of healthcare resources. That makes it more desirable because there isn't any direct competition.

    Utility: 

    Deep Funding's objective of improving platform utility is in line with the significant scheduling decision benefits that the inclusion of causality detection AI delivers.

    Success Factors:

    1. Comprehensive Approach: The project covers various healthcare scheduling aspects, offering a holistic solution.
    2. Regulatory Compliance: Emphasizing HIPAA and GDPR adherence instills trust and ensures ethical practices.
    3. Iterative Development: Prototyping and testing phases reflect a commitment to refining solutions for optimal outcomes.
    4. Stakeholder Engagement: Incorporating feedback from healthcare professionals and investors ensures practicality and market relevance.

    Recommendations for Effective Delivery:

    1. Prioritize Data Scientist Recruitment: A dedicated expert can enhance data analysis, crucial for effective AI-driven decisions.
    2. Emphasize User Experience: Iterative testing should focus on user feedback to ensure intuitive system usability.
    3. Regulatory Oversight: Continuous monitoring of compliance with healthcare regulations is vital for trust and legality.
    4. Collaboration Opportunities: Seek partnerships within the healthcare industry for real-world testing and validation.

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    musondabemba
    May 9, 2024 | 2:50 PM
    Project Owner

    Thank you for providing your review. It's gratifying to see recognition of the potential impact of our Health Causal Innovations proposal on healthcare scheduling system optimization. I appreciate the acknowledgment of our project's viability & alignment with market demands, along with the insightful recommendations for improvement, particularly regarding the recruitment of a data scientist and emphasizing user experience. This feedback reinforces our commitment to refining our solution for optimal outcomes and ensuring its practicality and relevance in the healthcare industry.

  • 0
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    BlackCoffee
    May 5, 2024 | 12:41 AM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 3
    • Usefulness 3
    Collecting data

    According to the team, how important is data collection for this proposal (especially after it is applied in practice). And when collecting data and processing it at the same time, is there any possibility of information data leaking to the outside? I think that data collection and processing should be done meticulously and supervised to ensure effectiveness.

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    musondabemba
    May 5, 2024 | 8:07 AM
    Project Owner

    Dear BlackCoffee,

    Thank you for your feedback on the importance of data collection in our proposal. We acknowledge the critical role data plays, especially post-implementation, & understand the necessity for meticulous supervision during both collection and processing stages to ensure effectiveness. Regarding your valid concern about data security, we will actively implement additional measures to safeguard against information leakage and uphold the integrity of our project. Your input is invaluable, and we are committed to addressing these concerns comprehensively. Thank you for your continued support & guidance.

    Best regards,
    Musonda Bemba

  • 0
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    Max1524
    May 2, 2024 | 2:45 PM

    Overall

    3

    • Feasibility 2
    • Viability 3
    • Desirabilty 3
    • Usefulness 4
    Consider practical feasibility

    The proposed idea is good.
    "Optimizing different aspects of healthcare" sounds ideal but in reality it is quite difficult to do, I mean it is difficult to develop all aspects comprehensively, even with positive results. technology combination. The team should review the feasibility of the proposal. If the implementation is focused on a smaller scale instead of on a large scale as currently, I think the feasibility will be higher.

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    musondabemba
    May 7, 2024 | 10:56 PM
    Project Owner

    Thank you for your perspective. While we understand your concern about the practicality of our proposal, we remain confident in its potential impact on healthcare optimization. We can, however, carefully assess the feasibility of our approach and explore strategies to address any challenges even on a larger scale.

  • 0
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    Joseph Gastoni
    Apr 30, 2024 | 3:31 PM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 2
    • Usefulness 3
    Strong value proposition but faces challenges

    The HealthCausal Innovations project has a strong value proposition but faces challenges in data acquisition, regulatory compliance, and achieving widespread adoption in the healthcare system.

    Feasibility:

    • Data Acquisition: Obtaining large-scale, high-quality healthcare datasets with diverse patient information is crucial.
    • Algorithmic Expertise: Developing and implementing complex causal inference algorithms requires expertise in machine learning and data science.
    • Regulatory Compliance: Ensuring compliance with data privacy regulations like HIPAA and GDPR is essential.

    Viability:

    • Market Adoption: Convincing healthcare providers and institutions to adopt a new AI-powered diagnostic tool might require extensive validation and pilot studies.
    • Integration Challenges: Integrating the solution seamlessly into existing healthcare workflows could be complex.

    Desirability:

    • Improved Diagnostic Accuracy: The potential for more accurate diagnoses is highly desirable for both patients and healthcare providers.
    • Data-Driven Approach: The focus on using large healthcare datasets for better diagnostics is a strong selling point.

    Usefulness:

    • Enhanced Patient Care: More accurate diagnoses can lead to better treatment plans and improved patient outcomes.
    • Reduced Healthcare Costs: Early and accurate diagnoses can potentially reduce unnecessary procedures and improve healthcare resource allocation.

    Besides, the project should consider:

    • Start with Specific Diseases: Focus on uncovering causal relationships for specific diseases with well-defined datasets initially.
    • Collaboration with Hospitals and Research Institutions: Partner with healthcare institutions to access data and conduct pilot studies to validate the solution.
    • Focus on Explainable AI: Develop AI models that can explain their reasoning behind diagnoses to build trust with healthcare providers.
    • Phased Implementation: Start with a minimal viable product (MVP) that integrates well with existing workflows for easier adoption.

    By addressing these points and focusing on building trust through rigorous validation and explainable AI, HealthCausal Innovations can potentially revolutionize healthcare diagnostics, leading to improved patient care and reduced healthcare costs.

     

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    musondabemba
    May 9, 2024 | 3:00 PM
    Project Owner

    Thank you for the thorough review. It's encouraging to see acknowledgment of our project's strong value proposition, despite the challenges highlighted. We're aware of the importance of data acquisition and regulatory compliance, and we're committed to addressing these issues. The suggestions regarding starting with specific diseases, collaborating with hospitals and research institutions, focusing on explainable AI & implementing a phased approach aligned with our strategic vision. We'll prioritize these recommendations to ensure the success of HealthCausal Innovations and its potential to revolutionize healthcare diagnostics.

  • 0
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    Aokishi
    Apr 30, 2024 | 5:09 AM

    Overall

    3

    • Feasibility 1
    • Viability 1
    • Desirabilty 4
    • Usefulness 4
    A potential project but not prove its feasibility.

    The team's vision and goals are quite great in wanting to find a disease diagnosis solution to replace traditional solutions. However, it is tough for me to believe in the feasibility and capacity of the team. The project's solutions are described a lot but are repetitive and general. I don't see any guarantee that the algorithms the team uses are advanced. I also haven't seen the team demonstrate how they will get different types of healthcare data. According my knowledge, healthcare data is confidential and not always readily available to a third party such as this team. To be honest, I don't know anything about the team like who they are, what their experience and background are. At the very least, the team should demonstrate their status to show me they have access to healthcare data. In addition, the project's ability to improve by continuously collecting and increasing various types of healthcare data is also an extremely big challenge. The last thing is that the team did not provide any specific timeline.

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    musondabemba
    Apr 30, 2024 | 11:27 AM
    Project Owner

    Dear  Aokishi,
    Thank you for your review and for expressing your concerns. We understand your skepticism and appreciate your feedback. 

    Regarding the feasibility and capacity of our team, rest assured that we are dedicated professionals with extensive experience in healthcare and technology. We will provide detailed information about our team members' backgrounds and expertise to reassure you of our capabilities.

    We acknowledge the need for clarity in describing our project's solutions and algorithms. We will revise our documentation to eliminate repetition and provide concrete evidence of the advanced algorithms we intend to use for disease diagnosis.

    Regarding healthcare data access, we are committed to adhering to all privacy regulations and will outline our strategies for obtaining various types of healthcare data transparently and ethically.

    As for the project's continuous improvement and timeline, we will provide a detailed plan that addresses these aspects, demonstrating our commitment to delivering a successful solution.

    We appreciate your patience and constructive criticism, and we are dedicated to addressing your concerns and delivering a project that exceeds expectations.

  • 0
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    thanhseven
    Apr 29, 2024 | 12:53 PM

    Overall

    3

    • Feasibility 2
    • Viability 3
    • Desirabilty 2
    • Usefulness 4
    Project solution

    The way the author applies AI to health diagnosis requires detailing where the diagnostic facilities are located. In my opinion, in terms of health, it is impossible to misdiagnose or misdiagnose. We hope that the proposed team will be able to present the operating principles of the project. Another thing about which project team members need to be recruited through which criteria needs to be clarified further.

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    musondabemba
    Apr 30, 2024 | 11:21 AM
    Project Owner

    Dear Thanhseven, 

    Thank you for your feedback on our project proposal. We appreciate your insights and understand the importance of clarity regarding our approach to health diagnosis using AI.

    Regarding the diagnostic facilities, we will provide detailed information about their locations and operational principles to ensure transparency and understanding of our project's methodology.

    In terms of team recruitment criteria, we will clarify the selection process and criteria for project team members to ensure transparency and accountability in our team-building efforts.

    We value your input and are committed to addressing these concerns to enhance the clarity and validity of our project.

Summary

Overall Community

3.4

from 9 reviews
  • 5
    1
  • 4
    2
  • 3
    6
  • 2
    0
  • 1
    0

Feasibility

2.7

from 9 reviews

Viability

3.1

from 9 reviews

Desirabilty

3.4

from 9 reviews

Usefulness

3.9

from 9 reviews