Artificial Intelligence in Healthcare

Abstract

Artificial intelligence is to reduce human cognitive functions. It is bringing an approach to healthcare, powdered by increasing the availability of healthcare data and rapid progress of analyst techniques. We can survey the current status of Artificial intelligence applications in healthcare and discuss its future uses. It is the most transformative technology of the 21th century. Healthcare has been identified as an early candidate to be revolutized by artificial intelligence technologies. This article aims for providing an early stage contribution with the decision making capacities of artificial intelligence technologies. The possible ethical and legally complex backdrop of the existing framework. I will conclude the present structures are largely fit to deal with the challenge of artificial intelligence are present will discuss clearly about the artificial intelligence contribution to the present health care. Artificial intelligence, machine learning, deep learning can assist with proactive patient care, reduced future risk and streamlined work processes.
 Keywords: Artificial intelligence, machine learning, clinical decision support.

Yapay Zeka ve Sağlıkta Yapay Zekanın Kullanımına Yönelik Sağlık Bilimleri Fakültesi Öğrencilerinin Görüşleri

“…Amerika'da yapay zeka platformunu onkoloji tedavilerini analiz etmek ve yapay zekanın daha az yan etkiye sahip ilaçlar tasarlayıp tasarlayamayacağını görmek için kullanıldığı bilinmektedir [5,8,9]. Bu örnek uygulamalar, yapay zekanın, bilgi işleyebilme yeteneği ile sağlıkta yanlış tanılama ve tıbbi hatalar sorununu büyük ölçüde çözebileceğini ve verimliliği arttırmak için tıbbi malpraktis oranını azaltıcı rolü olan araçlar olarak kullanılabileceğini bildirmektedir [10,11]. Sağlık hizmeti sunumunda ve tıbbi araştırmalarda yapay zeka tekniklerinin potansiyel rolleri daha belirgin hale gelse de, pek çok yapay zeka uygulamasının tam olgunluğu henüz gerçekleşmemiştir.…”

Intriguing of pharmaceutical product development processes with the help of artificial intelligence and deep/machine learning or artificial neural network

“…The DL consists of a neural network of multiple layers that aim to emulate how the information processing is carried out by the human brain after understanding complicated patterns and feature interactions. In practical situations, deep learning helps to give structure to unstructured data and enables machines to learn to classify data without assistance (Abhinav & Subrahmanyam, 2019;Gilvary et al 2019).The ML is a subset of AI utilizing algorithm models and uses statistical methods with the ability to learn with or without being explicitly programmed (Abhinav & Subrahmanyam, 2019).It should be added that the AI & D/ML or ANN is based on a non-linear concept to study the independent factor's in uence on response variables. Non-linearity refers to a massive parallel network distributed throughout that allows for approximation and real-time operation to exhibit unpredictability and random behaviour.…”

A comparison of machine learning algorithms in predicting COVID-19 prognostics

“…Machine Learning (ML) algorithms have supported clinical decision-making [ 15 – 18 ]. ML algorithms are built on statistics and used in healthcare to diagnose diseases and develop prognostic models.…”