Re$-$Write my information must be in the style of an annotated bibliography. $1.)1.)$ Raskar R$,$ Tse DS$,$ Shah P$.(2019).$ The Past, Present, and Future of Artificial Intelligence in Healthcare. JAMA Network Open, $2(11),$ e$1911322.$

Summary: The authors discuss the potential of artificial intelligence $($AI$)$ to revolutionize healthcare by improving diagnostic accuracy, enhancing treatment planning, and streamlining administrative tasks. They acknowledge the ethical and regulatory concerns related to AI implementation in healthcare, such as algorithmic bias and patient privacy.

Explanation: AI has the capability to perform tasks that require human intelligence, including visual perception, decision$-$making, and language translation. In healthcare, AI can analyze vast amounts of medical data to identify patterns and make predictions, leading to personalized treatment plans for patients. However, concerns exist regarding algorithmic bias and the need for data security.

Final thoughts: While AI offers significant benefits for healthcare, its development must consider ethical and regulatory issues. The authors propose a research agenda focused on developing unbiased, transparent, and accountable AI systems, as well as establishing robust privacy and security measures for patient data. $2.)2.)$ Abu$-$Hanna, A$.,$ & Park, H$.-$A$.(2019).$ Artificial intelligence in healthcare: A critical review of the benefits, adoption, and challenges. International Journal of Medical Informatics, $130,104021.$

Summary: This paper offers a comprehensive review of the current state of artificial intelligence $($AI$)$ in healthcare. The authors highlight the benefits of AI in healthcare, including improved diagnostic accuracy, personalized treatment, and cost reduction. They also discuss factors influencing AI adoption, such as technological infrastructure, data quality, and regulatory issues. Additionally, the paper addresses challenges and risks associated with AI implementation, such as algorithmic bias and privacy concerns.

Benefits of AI in healthcare: AI can enhance diagnostic accuracy by analyzing large volumes of patient data and identifying patterns that may be missed by human experts. It can also offer personalized treatment recommendations by considering individual patient data, including genetics, lifestyle, and environmental factors. Furthermore, AI can help reduce healthcare costs by improving efficiency and reducing errors, leading to lower hospital readmission rates and shorter lengths of stay.

Factors influencing AI adoption: The adoption of AI in healthcare is influenced by factors such as technological infrastructure, including high$-$speed internet and computing resources. Data quality is also crucial, as high$-$quality data is needed to train and validate AI algorithms. Regulatory issues, such as data privacy and security, also play a significant role in the adoption of AI in healthcare.

Challenges and risks of AI in healthcare: One of the main challenges of AI in healthcare is algorithmic bias, which can occur when AI systems are trained on biased data sets. Privacy concerns are also significant, as AI systems may require access to sensitive patient data. Additionally, the paper discusses ethical considerations, such as the potential for job displacement and the importance of transparency and accountability.

Final thoughts: This paper provides a comprehensive overview of the current state of AI in healthcare and highlights both the opportunities and challenges associated with its implementation. It is a valuable resource for healthcare professionals, researchers, and policymakers interested in understanding the potential of AI in healthcare and the issues that need to be addressed to ensure its successful adoption.