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We examined the effectiveness of machine learning algorithms in improving time series healthcare metrics for heart rate data transmission (accuracy and efficiency) Thus, this paper aims at offering a synthesis of the subject of ml in healthcare, thereby exposing its importance and relevance. In this paper, we reviewed several machine learning algorithms in healthcare applications.

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Paper identifies and discusses the significant applications of ml for healthcare Machine learning (ml) is one of the key driving forces in the development of new technologies and is used in healthcare in various ways Artificial intelligence and machine learning (ml) have to the potential to improve health outcomes and increase healthcare system’s efficiency

A systematic literature review (slr) identified 220 published slrs evaluating ml applications in healthcare settings covering 10,462 ml.

Data current as of october 2025 30 october 2025, data source This extensive literature review investigates the integration of machine learning (ml) into the healthcare sector, uncovering its potential, challenges, and strategic resolutions. The increasing availability of data and computing power has made machine learning (ml) a viable approach to faster, more efficient healthcare delivery.

It is essential in several areas, such as healthcare and medical data protection Ml is applied to analyse medical records and disease forecasts.