Party-Rock Hackathon Project: Cyto Sherlock
Pathologist Assistant: AI-Powered Tissue Analysis and Diagnosis Aid
Published Feb 14, 2024
Last Modified Feb 16, 2024
Dim lights, weary eyes, a tide of tissue samples - pathologists, our medical detectives, drown in data fatigue. Each biopsy, a life-or-death riddle, yet delays mount, diagnoses falter. Burnout looms, a silent crisis threatening the accuracy we depend on. Missed clues mean dimmed prognoses, delayed interventions, shattered lives.
Cyto Sherlock, an AI assistant for analyzing patient tissue. Here is what out AI does:
- Generates a detailed diagnostic report
- Generates Recommended Procedures after diagnosing .
- Personalized chatbot based on the the patient history diagnostic reports and procedures done .
- Professionals can ask and get more insights on the patient case and if any issue is being un-noticed while diagnosing .
It has the potential to create a positive impact on various communities within the healthcare ecosystem:
For Pathologists:
- Reduced workload and fatigue: Automating mundane tasks like initial analysis and report generation can free up pathologists' time for complex cases and research.
- Improved accuracy and efficiency: AI can assist in identifying subtle patterns and reducing human error, potentially leading to more accurate diagnoses and faster turnaround times.
- Enhanced learning and training: The personalized chatbot feature can provide case-specific insights and answer questions, aiding in continuous learning and improving diagnostic skills, especially for students and residents.
For Patients:
- Earlier and more accurate diagnoses: Faster analysis and potential improvement in accuracy could lead to earlier interventions and better treatment outcomes.
- Reduced healthcare costs: Streamlined workflows and potentially fewer misdiagnoses could contribute to cost reduction in the healthcare system.
- Increased access to expertise: Cyto Sherlock could be particularly beneficial in areas with limited access to pathologists, providing patients with a second opinion or additional insights.
For the Healthcare System:
- Improved patient care
- Increased efficiency and resource allocation
Main objective
Faster diagnoses, personalized chatbots answering questions, and increased access to quality care in remote areas are all part of this vision. AI can empower patients and free up pathologists to provide focused care for complex cases.
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Sample input:
Age:55
Gender :Female
Biopsy type: Breast
Tissue Description:
This breast biopsy sample comes from a 55-year-old woman with no significant medical history.
The tissue is firm and white, with a single, well-circumscribed mass measuring 1.5 cm in diameter.
Microscopically, the cells are predominantly arranged in sheets and show mild nuclear pleomorphism.
The nuclei are slightly enlarged and hyperchromatic, with occasional mitotic figures observed.
The stroma is dense and shows minimal inflammatory infiltrate.Further Plans: Is to include the microscopic image of the the tissue for analysis.
Adoption of our ai with a perspective of assistant to help would bring a huge positive impact in daily healthcare ecosystems.
Give it a try and recommend it if you like it .Share and support .Open for feedback.
Project video link:
Project Trial link:
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