Mixed-methods design evaluates AI-based diagnostics and dietary systems, highlighting ethical considerations in healthcare.
Artificial Intelligence (AI) can change healthcare by transferring clever applications to diagnose better, helping with personalized healthcare, and streamlining health outcomes. The presented research develops and tests an AI-based healthcare application that will have two core features: A multi-disease detecting program on the critical organs (diabetes, kidney, heart, liver, breast cancer, malaria, pneumonia, and lungs) and an AI-based dietitian and food recommending system, which will provide some customized nutritional advice. The study will evaluate the validity, reliability, and usefulness of such systems, as well as the ethical and social implications of the same through a mixed-methods design. Multi-disease detection model has accuracy of 92.5 percent with organ specific accuracy spread between 71.17 percent (liver) to 99.17 percent (kidney). The AI dietitian app was found to match the expert recommendations with 98.9 accuracy and delivered health outcomes with 78 percent of the patients. In spite of these improvements, obstacles that include information privacy, the ease of algorithms, and the possibility of biases imply the requirement of effective ethical models. This paper highlights the transformative aspect of AI in the healthcare sector but also affirms that innovative use must be ethical to overcome ethical and practical concerns
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Yaseen et al. (2025) studied this question.
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