Multimodal Disease Prediction: A Hybrid Approach Combining Machine Learning, Deep Learning, YOLO, and SAM for Diverse Disease Detection

The healthcare industry faces significant challenges due to fragmented data systems, which impede the ability to obtain a comprehensive view of a patient's health history. Diagnosing multiple conditions accurately is complicated by overlapping symptoms and the presence of comorbidities, necessitating complex care management. Resource constraints, particularly in rural and underdeveloped areas, delay diagnosis and treatment, while variability in clinical expertise leads to inconsistent care quality. Furthermore, many patients are unable to afford modern diagnostic tests due to their excessive costs. This paper introduces an approach that presents a comprehensive healthcare platform, utilizing advanced deep learning algorithms for the early and accurate prediction of multiple diseases. By consolidating data and predictions in a single interface, it provides a holistic view of a patient's health, enhancing diagnostic efficiency and speed. The system's comprehensive disease coverage addresses overlapping symptoms, facilitating better management of comorbidities. This integrated approach not only improves patient outcomes by enabling timely interventions but also offers a cost-effective solution by reducing the need for multiple, expensive diagnostic tests. Our findings indicate that the integrated approach not only improves diagnostic accuracy but also provides a user-friendly interface for patient interaction, thereby contributing significantly to the early detection and management of multiple diseases. Through this analysis, YOLOv10 demonstrated a recall of 0.828. The system achieved a prediction accuracy of 0.9 for obstructive pulmonary disease, 0.98 for brain stroke, 1.0 for diabetes and thyroid disease, 0.84 for heart disease, and 0.99 for liver disease. This system, which makes preventive and individualized medical treatment possible, has the potential to completely transform the way healthcare is provided.