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  1. 18 nov. 2022 · These obstacles arise at all levels of AI adoption, including data collecting, technological development, clinical application, and ethical and societal concerns. This paper enlightens the drawbacks of AI in the healthcare industry besides its benefits.

  2. 14 nov. 2019 · Risks and challenges. While AI offers a number of possible benefits, there also are several risks: Injuries and error. The most obvious risk is that AI systems will sometimes be wrong, and...

  3. 29 feb. 2024 · Medical AI can cause data privacy concerns, bias in algorithms, and the need for rigorous validation. Ensuring ethical use, addressing technical limitations, and maintaining human oversight are crucial for successful integration and realizing AI's benefits in healthcare.

  4. 8 feb. 2023 · These obstacles arise at all levels of AI adoption, including data collecting, technological development, clinical application, and ethical and societal concerns. This paper enlightens the drawbacks of AI in the healthcare industry besides its benefits.

  5. 26 mar. 2021 · Problems and challenges. The inherent challenges of machine learning, the imperfection of ethics and laws, and the poor acceptance by society have all hindered the development of AI. Ethical issues. Data ethics.

  6. Safety is one of the biggest challenges for AI in healthcare. To use one well-publicized example, IBM Watson for Oncology uses AI algorithms to assess information from patients’ medical records and help physicians explore cancer treatment options for their patients.

  7. 11 nov. 2020 · “Once again medicine is slow to the mark. I’m no longer irritated but bemused that my kids, in their social sphere, are using more advanced AI than I use in my practice.” But even those who see AI’s potential value recognize its potential risks. Poorly designed systems can misdiagnose.

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