How Machine Learning Is Used to Detect Malignancies

 

The Medical Industry was one of the first to embrace AI, Machine Learning and Deep Learning for improving accuracy in diagnostics. Now, it is paying rich dividends, as it has become easy to detect malignancies with an accuracy of over 94 to 95 percent for most of the ailments.

Doctors used to just trust their knowledge, experience and intuition while detecting malignancies. But now with the use of AI, Machine Learning and Deep Learning, AI-powered machines can identify malignancies quite early to improve prognosis.

AI and Machine Learning to Detect Malignancies

Researchers have used AI and Machine Learning to detect metastatic lymph nodes to identify cancers by analyzing PET/CT images of lymph nodes. This not only detects cancers but also helps provide the best treatment and avoid treating patients more than necessary

AI and Machine Learning will also help doctors make decisions on whether to provide chemotherapy and radiation therapy or provide surgical treatment for each type of cancer. Accuracy in diagnosis of metastatic lymph nodes can also help doctors provide only as much radiation as required to treat or cure the malignancy.

Before the use of Machine Learning, a doctor might not have been able to diagnose smaller metastasized lymph nodes. They had to rely on larger nodes that looked typically malignant. So, relying on the clinician’s experience alone did not prove to be as accurate as AI or Machine Learning were or could be.

Machines are taught to diagnose lymph nodes by showing hundreds of images of lymph nodes. They are, then, made to classify these lymph nodes based on metrics as size, texture, etc. It also uses a 3D Convolutional Neural Network (CNN), a type of Deep-Learning Neural Network, to identify and classify the nodes based on their features.

Combining Machine Learning with conventional Radiomics also creates a hybrid approach to diagnosis of malignancies. The CNN-Radiomics hybrid model is found to be more accurate than either a standalone CNN model or a mere Radiomics model alone.

What This Means For The Medical Industry

It is just a matter of time before the medical industry will begin using Machine Learning to benefit from the accuracy it provides. Machine Learning will also benefit the medical industry in all possible ways including diagnosis, treatment and improving patient prognosis to prolong the lifespan of human beings.

It is also high time that these technologies got incorporated and combined with conventional technologies in the field of medicine. So, if you are part of the medical industry, be sure to have AI and Machine Learning incorporated in your healthcare business.

We are adept at incorporating AI and Machine Learning technologies in the field of medicine and the healthcare industry. So, please write to us at sales@twilightsoftwares.com and visit www.twilightitsolutions.com to learn more of our expertise in AI and Machine Learning and what we can do for you and your medicine/healthcare business.

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