• PRAVEENA A
• R.Kiran Sri
• Shaik Naseer
• V.Venkata Sai Krishna
• V.Venkata Prasanna Kumar

A deep learning approach for health analysis leverages algorithms like CNN, logistic regression, random forest etc. to extract valuable insights from medical data. By employing deep neural networks, this methodology can effectively analyze complex medical datasets, including patient records, imaging scans, and more. Through sophisticated pattern recognition and feature extraction, deep learning models can detect and predict outcomes, and even assist in diagnosis and treatment planning. This technology holds immense potential for revolutionizing healthcare by enabling personalized medicine, early disease detection, and optimized treatment strategies. Overall, deep learning in health analysis offers a powerful toolset for healthcare professionals, researchers, and policymakers to improve patient care, advance medical research, and enhance public health initiatives.

"Health Analysis Mentor", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.e6-e12, May-2024, Available :http://www.jetir.org/papers/JETIR2405402.pdf

"Health Analysis Mentor", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppe6-e12, May-2024, Available at : http://www.jetir.org/papers/JETIR2405402.pdf