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2000
Volume 21, Issue 18
  • ISSN: 1570-1808
  • E-ISSN: 1875-628X

Abstract

Artificial Intelligence (AI), due to digitalization, has recently conquered the healthcare disciplines. AI has substantially progressed in healthcare and medical research for preventive, predictive, and personalized care. AI will continue to become the ultimate healthcare-effective tool for serious ailments requiring the early detection of rebuttal. It is a fast-growing automated system based on algorithms positioned to benefit patients, clinicians, researchers, and physicians involved in treatment, prognosis, and preventive care in health. The primary focus of artificial intelligence is technologically expedited solutions to complex challenges. AI's remarkable contribution to machine learning has become a transforming opportunity in medical science. The optimized research, formulation, and development in AI reduce the cost of medical therapy, provide extensive care, improve patient compliance, and promote personalized medicine. The articles were cited from SCI-hub, PUBMED, Scopus, and Google Scholar. AI is assisted with autonomous disease assessing and screening tools that can save time for clinicians and help in the early diagnosis of diabetic retinopathy, cancer detection, and chromosomal disorders to solve complex hurdles. The automated image quality improvement tool makes AI an effective medium for targeting highly complex drug molecules and specific sensors to target organs. Furthermore, the masses have utilized their application in medical devices, pharmaceutical technology, dosage form designing, medical research, and regulatory frameworks to explore the medical era of AI in the healthcare field. However, the integration of AI in medical practice is in the early stages and needs further research to fit an AI model-based approach in clinical settings. AI limitations in health and medical research arise from biases related to gender variation, ethical concerns, complex algorithms, regulatory, cyber security, model evaluation, and problems faced by policymakers. Certain vulnerability factors that can cause health record data breaches and ethical concerns present challenges in healthcare settings due to result failure. Therefore, solutions to overcome these challenges are essential to set the future of AI in clinical research. All such concerns and their solutions must be successfully deployed from research to clinical settings to adopt transformative AI models in medical science. This will help scientists and researchers explore lead molecules and identify newer therapeutic targets. It is crucial to implement measures to control and frame policy guidelines, conduct continuous checks on cybersecurity, solve ethical issues, and consider the possibility of AI adoption in pharmaceutical industries, banking, research areas, hospitals, administration, and clinical practice.

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Exploring the Potential of Artificial Intelligence in Medical Research: Applications, Regulatory Concerns, Opportunities and Future Outlook- A Mini Review
Letters in Drug Design & Discovery 21, 4205 (2024); https://doi.org/10.2174/0115701808342987241216081153
/content/journals/lddd/10.2174/0115701808342987241216081153
/content/journals/lddd/10.2174/0115701808342987241216081153
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  • Article Type:     Review Article
Keyword(s): algorithms; Artificial intelligence (AI); clinical setting; drug delivery; health care; medical research; patient care; personalized medicine

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