harmful side effect
Artificial Intelligence tool could reduce common drug side effects: Artificial intelligence could help clinicians assess which patients are likely to encounter the harmful side effects of some commonly used antidepressants, antihistamines and bladder medicines.
Anticholinergic side effects include confusion, blurred vision, dizziness, falls and a decline in brain function. Anticholinergic effects may also increase risks of falls and may be associated with an increase in mortality. They have also been linked to a higher risk of dementia when used long term. Now, researchers have developed a tool to calculate harmful effects of medicines using artificial intelligence. The team created a new online tool, International Anticholinergic Cognitive Burden Tool (IACT), is uses natural language processing which is an artificial intelligence methdolody and chemical structure analysis to identify medications that have anticholinergic effect.
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Artificial intelligence model "learns" from patient data to make cancer treatment less toxic
MIT researchers are employing novel machine-learning techniques to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for glioblastoma, the most aggressive form of brain cancer. Glioblastoma is a malignant tumor that appears in the brain or spinal cord, and prognosis for adults is no more than five years. Patients must endure a combination of radiation therapy and multiple drugs taken every month. Medical professionals generally administer maximum safe drug doses to shrink the tumor as much as possible. But these strong pharmaceuticals still cause debilitating side effects in patients.
Artificial Intelligence Uses "Self-Learning" to Make Cancer Treatment Less Toxic
MIT researchers aim to improve the quality of life for patients suffering from glioblastoma, the most aggressive form of brain cancer, with a machine-learning model that makes chemotherapy and radiotherapy dosing regimens less toxic but still as effective as human-designed regimens. Machine-learning system determines the fewest, smallest doses that could still shrink brain tumors. MIT researchers are employing novel machine-learning techniques to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for glioblastoma, the most aggressive form of brain cancer. Glioblastoma is a malignant tumor that appears in the brain or spinal cord, and prognosis for adults is no more than five years. Patients must endure a combination of radiation therapy and multiple drugs taken every month.