Abstract : This review discussed the artificial intelligence techniques used in the medical examination, the models used for artificial intelligence algorithms in the medical examination, how the data were classified, as we gain a deeper understanding of disease biology and how diseases affect an individual, so, we provided an overview of the research related to the use of models used for artificial intelligence algorithms in the detection of human diseases and also compared the results obtained through artificial intelligence techniques, and how effective those algorithms were in medical detection and prediction. of recent research in the areas of Breast Cancer, Diabetes Disease, DR, Lung Cancer, Diabetes mellitusm, COVID19, Heart disease, Diabetes diagnoses, Cervical Cancer and Phthalic acid. there is a need for artificial intelligence (AI) to be able to support predictions for personalized treatments. Healthcare applications and systems are being introduced along with the adoption of cloud computing in healthcare so, medicine has entered the digital age with data from new modalities, as well as new sources such as wearables and the Internet of Things.

Keywords: Diabetic Retinopathy (DR); Deep learning (DL); K-SVM-related algorithms generated (K-means and sup - port vector machine); Deep learning-based measure (DML); Consecutive Long-Term Memory Model (CSO-CLSTM).