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How machine learning algorithm help in cancer research

 

Cancer is a fatal spread to humans as it is neither easily detectable nor easily cured. The worth of cancer research and development and its cure is expected to reach 25 billion dollars globally by 2030. AI with all of its gadgets transforming the health sector with great potential. Artificial intelligence, machine learning and deep learning revolutionized cancer research and its treatment.

One of its many great achievements is the reduction in time or reduce the time of research which able researchers to go on with accuracy. Machine learning emphasizes cancer treatment by early diagnosis. It enables healthcare workers to detect cancer at an undetectable stage and time.

Easy and early detection, diagnosis and prognosis of cancer.

Machine learning algorithms can be trained to learn and visualize medical images like x-rays, MRI and city scans which helps in the detection of cancer cells with efficiency and accuracy. This helps health care workers exceptionally in the early detection of cancer disease in the patient; results in early initiation of the cure of the patient and enhance the survival chances of the patient significantly.

Genomic analysis and Personalized treatment plan.

Artificial intelligence and machine learning are able to examine or investigate huge genomic sets of data to reveal mutations in normal bodies or that are related to cancer. Genomic analysis helps doctors to make target oriented therapy for the cancer cure of the patient; improved target oriented therapies are significantly more effective than vice versa.

It is artificial intelligence and machine learning which capable healthcare workers to make an accurate personalized treatment plan for the patient with higher efficiency after the analyses of the patient’s data, previous medical history, genomic identification and genetic information of the patient. It also analyses any previous treatment of the patient and its outcomes on the patient before making a personalized treatment plan. Hence it reduces the cost of cancer cure and helps in effective and better cure.

Drug discovery research and development.

Large databases of chemical (lifesaving drugs related) compounds are analyzed through machine learning algorithms to investigate the ones which are most likely to be effective in treating cancer. The possible number of patterns of curative drugs and their accurate doses are too high in numbers to determine it manually; it is a slow process that takes lots of manpower, time and cost which increases the cost of cancer cure but by using machine learning tactics of artificial intelligence it is quick faster than traditional way and cost effective and accurate. This can facilitate the accurate and more effective identification of new life saving drugs by researchers.

Clinical trials and their optimization.

Patient demographics, treatment regimens, and goals are the base of using machine learning algorithms; that are used to optimize clinical trial studies and research. This assists researchers in conducting trials that are more effective, efficient and accurate and results in new discoveries of cancer treatments. In a nutshell, machine learning helps in hastening cancer research by delivering fresh perspectives, enhancing precision, prompt results and hastening the creation of novel medicines.

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