A Survey on Machine Learning Techniques for Medical Report Analysis

Using machine learning and deep learning techniques, inte-ligent prediction of diseases, clinical text analysis, and auto-matic report generation have been achieved. This literature review article focuses on research papers published in the years 2021–2026 regarding the application of machine learn-ing algorithms in health care systems. Machine learning and deep learning algorithms such as SVM, Random Forest, CNN, RNN, LSTM, and Transformer models have been dis- cussed, along with their applications, benefits, and drawbacks. There are some notable challenges such as data privacy, inadequate data sets, lack of explainability, imbalance in data sets, and computation. Despite the presence of these chal- lenges, there is still room for future development of intelli- gent health care systems in terms of multimodal learning, explainable AI, and generative AI. Intelligent analysis systems of machine learning-assisted medical reports can help in increasing the efficiency of health care services, reducing mistakes made dur-ing diagnosis, and aiding healthcare professionals in decision making.

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