Evolution of Machine Learning in Tuberculosis Diagnosis: A Review of Deep Learning-Based Medical Applications

Tuberculosis (TB) is an infectious disease that has been a major menace to human health globally, causing millions of deaths yearly. Well-timed diagnosis and treatment are arch full recovery the patient. Computer-aided (CAD) hopeful choice for TB diagnosis. Many CAD approaches using machine learning have applied diagnosis, specific artificial intelligence (AI) domain, which led resurgence AI in medical field. Deep (DL), branch AI, provides bigger room diagnosing deadly disease. This review focused on limitations conventional diagnostics broad description various algorithms their applications Furthermore, deep methods integrated with other systems such as neuro-fuzzy logic, genetic algorithm, immune discussed. Finally, multiple state-of-the-art tools CAD4TB, Lunit INSIGHT, qXR, InferRead DR Chest summarized view AI-assisted future aspects