Application of Artificial Intelligence Techniques in Healthcare
- Authors: Bhavana Singh1, Amrish Chandra2, Deepika Joshi3, Nidhi Semwal4, Gauree Kukreti5, Urvashi Saxena6
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View Affiliations Hide Affiliations1 School of Pharmacy, Sharda University, Knowledge Park III, Greater Noida, UP, 201310, India 2 School of Pharmacy, Sharda University, Knowledge Park III, Greater Noida, UP, 201310, India 3 Graphic Era Hill University, Dehradun, 248001, UK, India 4 SGRR University, Dehradun, 248001, UK, India 5 School of Pharmaceutical Sciences and technology, Sardar Bhagwan Singh University, Balawala, Dehradun, 248161, UK, India 6 TMCOP, TMU, Moradabad, 244001, UP, India
- Source: AI in the Social and Business World: A Comprehensive Approach , pp 67-101
- Publication Date: October 2024
- Language: English
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The integration of Artificial Intelligence (AI) into healthcare promises improved medical evaluation, provided therapeutic solutions, and enhanced patient care. Various AI branches, including machine learning, deep learning, and computer vision, adeptly handle vast healthcare datasets ranging from electronic health records to wearable data. These techniques extract vital patterns, forecast early-stage diseases, and personalize patient treatments. In diagnostics, AI tools excel at identifying diseases and predicting patient outcomes by automating image readings and pinpointing health risks. AI also optimizes healthcare logistics, resource allocation, and overall patient care, reducing clerical tasks and promoting data-driven decisions. Yet, there are challenges. Concerns about data privacy, legislative compliance, ethics, and the need for transparent AI results are paramount. Addressing these is crucial for successful AI integration in healthcare. In essence, AI's integration into healthcare promises revolutionary diagnostic and therapeutic advances. Navigating the challenges requires collaboration between medical experts, AI specialists, lawmakers, and ethicists to fully realize AI's transformative potential.
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