Journal of Clinical and Experimental Toxicology

Deep Learning technology in medical science

Joint Event on International Conference on Toxicology, Clinical Toxicology & Pharmacology & 6^th International Conference on Recycling & Waste Management
December 03-04, 2018 | Dubai, UAE

Kamal Kumar Sharma

Lovely Professional University, India

Scientific Tracks Abstracts : J Clin Exp Tox

DOI: 10.4066/2630-4570-C1-002

Abstract:

Health is a term used for mental and physical well-being. Lifestyle, geographical region, diet, physical activity determines the quality of life. Disease is nothing but excessive growth or decay of cells in the body that degrades the mental and physical health. Health monitoring is a challenging task as it needs regular check-up, in-depth analysis of reports, diagnosis and final drug dispersal. History of medical treatment can significantly fast track this process. Electronic health records can play a significant role in it. Pervasive sensors like wrist band can change the way medical data is collected providing proactive, predictive & participatory health. The updated data can be transmitted to the experts for diagnosis and prescription. Not only this, medical imaging can be used for drug discovery, drug amount dispersal, toxicology, precision medicine. Medical imaging has emerged as a significant tool in the early diagnosis of disease associated with different parts of the body hence improve the drug delivery and care to the patient. Electronic Health Report (EHR) can play significant role in it keeping track of medical dosage. Combined effects of various factors like age, medical history, allergy to certain drugs, geographical factor etc. can be studied for better diagnosis and drug- dispersal. Drug approval takes 15 years of testing and FDI approval. medical imaging can fast track the process. Drug testing & validation from regulatory body takes 15 years. The application of medical imaging in pharmaceutical clinical trials involves its use to determine disease predisposition; to identify likely responder patients; to diagnose lesions and evaluate their severity; and to monitor therapy effects and follow-up. Considerable emphasis has also been placed on linking pre-clinical imaging and clinical data in order to increase the success rate of clinical trials (1). Pre-clinical imaging in appropriate disease animal models can contribute to the identification of new imaging biomarkers, whereby histological correlation can be obtained. It is anticipated that greater use of imaging during pre-clinical stages will facilitate better translation from animal models to human subjects.

Biography:

Kamal Kumar Sharma is a technology veteran with 17+ years in academics and administration. He is an Electronics and Communication Engineer and is passionate about competency developments in these areas. He belongs to Haryana and working as Professor in Lovely Professional University, Punjab. 

E-mail: kamalsharma111@gmail.com

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