Transforming healthcare: the impact of artificial intelligence on diagnostics, pharmaceuticals and ethical considerations - a comprehensive review.

Journal: International journal of surgery (London, England)
Published Date:

Abstract

Interpretability of results remains challenging in most health industries since patients may suffer life-threatening consequences from an inaccurate diagnosis. Artificial Intelligence (AI) integration has arisen as a prominent technology in the healthcare sector, transforming the field by advancing early diagnostics, surgeries, and ethical concerns. The present review analyses the multidimensional impact of AI on the health sector through enhancements in medical accuracy and diagnosis outcomes. Implementing AI techniques and machine learning algorithms in predictive analytics enables disease identification at a nascent stage, boosting decision-making accuracy. Advancements in genomics have demanded the employment of AI in decoding genetic information supporting personalized and targeted treatments. The review comprehensively examines the application of AI-based diagnostics addressing the impact on heart-associated diseases, cancer pathogenesis, and other general disease prediction. Different machine learning algorithms aid in identifying tumor behavior, risk factors, and tailored therapy in cancer treatment. In the context of cardiovascular disorders, AI-driven methodologies aid in assessing the patient data, risk factors, and forecasting the probable complications in preventative care. AI-based surgeries employing the da Vinci system highlight the use of AI in increasing the prediction of surgical success rate. Robotic automation in orthopedics advances spine and joint replacement surgeries, offering real-time guidance and enhancing patient recovery outcomes. Broader improvements in AI integration in healthcare have been discussed, focusing on refining algorithms for improved application.

Authors

  • V C Deivayanai
    Department of Biotechnology, Saveetha School of Engineering, SIMATS, Chennai 602105, India.
  • Pavithra Swaminaathan
    Department of Biotechnology, Saveetha School of Engineering, SIMATS, Chennai, India.
  • A S Vickram
    a Industrial Biotechnology Division , School of Biosciences and Technology, VIT University , Tamil Nadu , India.
  • A Saravanan
    Department of Biotechnology, Saveetha School of Engineering, SIMATS, Chennai 602105, India. Electronic address: sara.biotech7@gmail.com.
  • Shabana Bibi
    Department of Biosciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan.
  • Navidha Aggarwal
    MM College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, India.
  • Virender Kumar
    International Rice Research Institute, Los Baños, Philippines.
  • Albaraa H Alhadrami
    Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Zuhair M Mohammedsaleh
    Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk, Saudi Arabia.
  • Rawan Altalhi
    Department of Biological Sciences, College of Science, University of Jeddah, Jeddah, Saudi Arabia.
  • May Nasser Bin-Jumah
    Biology Department, College of Science, Princess Nourah bint Abdulrahman University.
  • Amany A Sayed
    Zoology Department, Faculty of Science, Cairo University, Giza, Egypt.
  • Amirah Albaqami
    Department of Clinical Laboratory Sciences, Turabah University College, Taif University, Taif, Saudi Arabia.
  • Hitesh Chopra
    Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai - 602105, Tamil Nadu, India.
  • Talha Bin Emran
    Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh.
  • Mohamed M Abdel-Daim
    Department of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College, P.O. Box 6231, Jeddah, 21442, Saudi Arabia; Pharmacology Department, Faculty of Veterinary Medicine, Suez Canal University, Ismailia, 41522, Egypt.

Keywords

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