How AI is improving the treatment of cancer

May 18, New Delhi There are now more options for treating cancer than only the conventional methods of chemotherapy, radiation treatment, and surgery. According to medical specialists on Saturday, artificial intelligence (AI) is making major advancements in cancer therapy that will help patients and clinicians achieve better results.

AI is proving to be a significant factor in the development of novel medications as well as in prognostic and treatment outcome prediction, according to medical specialists. It may also facilitate the development of customized medication.

Concerns about patient data privacy, safety, and ethical usage still exist, however.

“I can declare with confidence that AI is no longer restricted to surgery, chemotherapy, radiation, or targeted treatment since I work as a surgical oncologist. It also has significant effects on biomedical cancer research and radiodiagnostics. The use of AI in biomedical cancer research is facilitating the development of novel drugs and therapies. “A crucial application we use for the early detection of oral cancers is image analysis, which makes it easier to detect cancer early,” said Raj Nagarkar, Managing Director & Chief of Surgical Oncology & Robotic Services of HCG Manavata Cancer Centre (HCGMCC) & Hospitals.

“Radio-imaging modalities are investigating AI computer vision models for cancer risk prediction and early illness detection. With encouraging findings, point-of-care diagnostics businesses are using AI algorithms for early detection. AVP of IT & Oncology at Apollo Hospitals Roheet Rao said, “We can definitely improve cancer care delivery by employing AI. Early detection of disease has a significant impact on outcomes.”

AI-enabled breast cancer screening, according to Raj, is also helping with therapy formulation and personalization.

Machine learning algorithms in CT scans and MRIs enhance imaging accuracy when it comes to radio diagnoses. AI-driven tools may improve segmentation and the diagnosis of various malignancies, especially in the context of CT, MRI, and mammography.

Artificial intelligence (AI) assessments of robotic or computer-assisted surgery are improving patient comfort, safety, and specificity of treatments.

Moreover, AI in chemotherapy improves and personalizes available treatment choices by analyzing datasets to create individualized treatment regimens based on molecular and genetic traits. According to Dr. Raj, predictive models may be created to assess patient reactions to certain regimens.

AI is also expanding the choices for treating cancer, including CAR T-cell therapy and immunotherapy.

“Deep learning models for cancer stem cell detection aid in early diagnosis and customising treatment plans, making AI a reality across all facets of oncology, from diagnosis and research to treatment,” Raj said.

Before we see a greater acceptance of AI in the provision of healthcare, there are hazards associated with its use that must be addressed.

“One of the key issues is data privacy, safety, and ethical use of patient data,” Roheet said.

Additionally, he drew attention to the bias present in AI models, which are produced by the training data.

“Unless there is validation of AI models across different types and cohorts of data, oncologists need to be mindful of such biases,” the physician told IANS.

To guarantee patient safety, the models’ accuracy and dependability must be extensively evaluated both before and after they are used in clinical settings. Regardless of the AI models being used, clinicians will always have the last word on clinical care since having a person in the loop is the best way to assure supervision when employing AI, the speaker pointed out.

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