Artificial Intelligence usage has been increasing across all industries including the medical community and has proven to be a useful tool in the field. AI uses data in a more effective manner through machine learning algorithms in order to produce positive patient outcomes. It helps automate time-consuming processes and enhances decision-making processes. Various healthcare applications have been developed where one can recognize the population at risk and make a more accurate diagnosis of the identified problem.
Taking a closer look, let’s concentrate on a major field of medicine- Cancer, and radiology. AI has proven to be extremely useful in the prediction, prevention, and treatment of cancer. Mammograms are not only being used to detect breast cancer, but also predict it. Studies show that mammograms reduce breast cancer mortality by avoiding the development of cancer undetected. Scientists in National Cancer Institute’s intramural research program helped develop an AI technology that detects precancerous lesions using digital images. The AI method resulted to be the most accurate. Another group of scientists trained a computer algorithm to analyze MRI images of the prostate. AI is being used to detect and interpret features of target molecules, make predictions for new drugs to target those molecules and help evaluate the effectiveness of those drugs. Research is also being done to identify novel approaches for creating new drugs more effectively. German scientists developed the methylation-based classifier that was trained to sort medulloblastomas into subtypes, eventually, the project expanded, and now around 60,000 types of tumours are available in the database. The system compares data to its reference list of tumours and places the profile into a group, but if it doesn’t quite match, cancer gets a low confidence score. Pathologists examine the low-scoring samples, and if there are at least seven with the same methylation profile, they assign them to a new group and retrain the classifier. The classifier now recognizes about 150 different cancer entities. The computer’s ability to spot those cancer types could cut hospitals’ error rates. In the initial study, the algorithm found that 12% of brain tumours had been misdiagnosed by pathologists. AI and ML can be used for personalized treatment and medicines by making use of the patient’s electronic health records, data from sensors, and wearables. By using medical history and the characteristics of the tumour, AI has the potential to come up with multiple treatment options for patients. Natural Language Processing techniques based on AI have shown potential in predicting the development of diseases across healthcare systems. AI can be used in drug development. There are multiple stages of drug discovery and AI can be used in new drug discovery by designing protein structures, target validation, and managing drug trials. It is expected that with the introduction of AI, not only will the costs of drugs reduce, but it will also enhance the drug discovery process, which currently takes as long as 10-15 years.
The examples given above are just the tip of the iceberg. AI has helped mankind take huge strides in the field of cancer. It has made results more accurate, recognition and prediction faster, and hence the mortality rate to go lower. The growth of AI has helped in the treatment of cancer greatly.
Sources:
https://www.dynam.ai/top-10-ai-applications-in-healthcare-and-the-medical-field/
https://healthitanalytics.com/news/deep-learning-model-for-mammograms-predicts-breast-cancer-risk
https://www.weforum.org/agenda/2021/02/cancer-treatment-ai-machine-learning
https://www.cancer.gov/research/areas/diagnosis/artificial-intelligence
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