Machine Learning and Deep Learning Methods for Building Intelligent
Systems in Medicine and Drug Discovery: A Comprehensive Survey
- URL: http://arxiv.org/abs/2107.14037v1
- Date: Mon, 19 Jul 2021 14:26:03 GMT
- Title: Machine Learning and Deep Learning Methods for Building Intelligent
Systems in Medicine and Drug Discovery: A Comprehensive Survey
- Authors: G Jignesh Chowdary, Suganya G, Premalatha M, Asnath Victy Phamila Y,
Karunamurthy K
- Abstract summary: Artificail Intelligence based framework is rapidly revolutionizing the healthcare industry.
These intelligent systems are built with machine learning and deep learning based robust models for early diagnosis of diseases.
This paper focuses on the survey of machine learning and deep learning applications in across 16 medical specialties.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: With the advancements in computer technology, there is a rapid development of
intelligent systems to understand the complex relationships in data to make
predictions and classifications. Artificail Intelligence based framework is
rapidly revolutionizing the healthcare industry. These intelligent systems are
built with machine learning and deep learning based robust models for early
diagnosis of diseases and demonstrates a promising supplementary diagnostic
method for frontline clinical doctors and surgeons. Machine Learning and Deep
Learning based systems can streamline and simplify the steps involved in
diagnosis of diseases from clinical and image-based data, thus providing
significant clinician support and workflow optimization. They mimic human
cognition and are even capable of diagnosing diseases that cannot be diagnosed
with human intelligence. This paper focuses on the survey of machine learning
and deep learning applications in across 16 medical specialties, namely Dental
medicine, Haematology, Surgery, Cardiology, Pulmonology, Orthopedics,
Radiology, Oncology, General medicine, Psychiatry, Endocrinology, Neurology,
Dermatology, Hepatology, Nephrology, Ophthalmology, and Drug discovery. In this
paper along with the survey, we discuss the advancements of medical practices
with these systems and also the impact of these systems on medical
professionals.
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