implementation requires computational power. It is often only available using cloud services.
In fact, with the increasing amount of data generated by sensors, the performance of ML-based cloud processing has several weaknesses for various reasons.
2.7 Recommendations and Consideration
AI in healthcare is ready to bring change and disrupt medical care. While not giving up marketing and profitability of drug addiction is the wisest guide, it balances AI, the need for comprehensive healthcare to plan and manage and reduce potential unexpected consequences.
It is wise to take. For AI, the best solution is to start with a real healthcare issue, involving the relevant stakeholders, first-line users, patients, and their families (including artificial and non-AI options). You need to find a solution and work on it. It is implemented and extended by our five goals: better health, better care experience, doctor health, lower cost, and common rights.
2.8 Conclusions
The nature of administration is significantly influenced by the nature of your internet association, making it difficult to use. Healthcare providers require shorter response times to address potential health risks, especially when performance such as early detection, risk prevention, and activity diagnosis is guaranteed in real time.
Because of the huge measure of individual data that should be overseen, data stockpiling and security are additionally vital when managing medical care. For all of this, choosing purely local administration, especially for mobility, is not yet practical due to limited processing and storage capabilities.
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*Corresponding author: [email protected]
