Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in Medical science and especially in Radiology. Some of the things which AI is capable of doing are:
Thoracic imaging: Lung cancer is one of the most common and deadly tumours. Lung cancer screening can help identify pulmonary nodules, with early detection being lifesaving in many patients. Artificial intelligence (AI) can help in automatically identifying these nodules and categorizing them as benign or malignant.
Abdominal and pelvic imaging: With the rapid growth in medical imaging, especially computed tomography (CT) and magnetic resonance imaging (MRI), more incidental findings, including liver lesions, are identified. AI may aid in characterizing these lesions as benign or malignant and prioritizing follow-up evaluation for patients with these lesions.
Colonoscopy: Colonic polyps that are undetected or misclassified pose a potential risk of colorectal cancer. Although most polyps are initially benign, they can become malignant over time115. Hence, early detection and consistent monitoring with robust AI-based tools are critical.
Mammography: Screening mammography is technically challenging to expertly interpret. AI can assist in the interpretation, in part by identifying and characterizing microcalcifications (small deposits of calcium in the breast).
Brain imaging: Brain tumours are characterized by abnormal growth of tissue and can be benign, malignant, primary or metastatic; AI could be used to make diagnostic predictions116.
Radiation oncology: Radiation treatment planning can be automated by segmenting tumours for radiation dose optimization. Furthermore, assessing response to treatment by monitoring over time is essential for evaluating the success of radiation therapy efforts. AI is able to perform these assessments, thereby improving accuracy and speed
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