Work

A Multi-modal Ai System for Automated Detection of Pneumonia, Skin Diseases, and Bone Fractures

Year: 2024

Type: article

Abstract: This paper presents a multi-modal AI-driven solution designed to aid healthcare professionals in diagnosing pneumonia, skin diseases, and bone fractures.Leveraging deep learning techniques, the system utilizes three distinct YOLOv8 models for image segmentation, classification, and object detection.The integration of large language models (LLMs) such as Google Gemini enhances diagnostic accuracy.The system includes two workflows: new diagnosis and second opinion, allowing patients and medical ex-perts to upload images and obtain refined results.Combining advanced AI, secure cloud storage, and an intuitive front end, the solution significantly improves diagnostic speed and accuracy.

DOI: 10.71058/jodac.v8i11010

Authors: Triumph AI, Mumbai, India, Aakash Walavalkar, wati Vaishnav, SVKM’s NMIMS – MPSTME, Mumbai, India, Jay Ajmera, SVKM’s NMIMS – MPSTME, Mumbai, India, Kallind Soni, SVKM’s NMIMS – MPSTME, Mumbai, India, Atharva Rode, SVKM’s NMIMS – MPSTME, Mumbai, India, Andrila Sarkar

Institutions: Narsee Monjee Institute of Management Studies, Shri Vile Parle Kelavani Mandal, University of Engineering & Management, Jaipur

Language: English

Topic: COVID-19 diagnosis using AI

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W4405865121

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