Vaishnavi Mishra, Sarita Ugemuge, Yugeshwari R. Tiwade
{"title":"Artificial intelligence changing the future of healthcare diagnostics","authors":"Vaishnavi Mishra, Sarita Ugemuge, Yugeshwari R. Tiwade","doi":"10.3233/jcb-230118","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) is a computer’s capacity to carry out operations like speech and image recognition and decision-making that ordinarily require human intelligence. Healthcare is using AI to automate tasks such as medical image analysis and diagnosis that require high precision and accuracy. The healthcare industry is significantly impacted by the rapid development of machine learning algorithms, which are frequently implemented using deep learning, as well as the growth of digital data and computing power supported by improvements in hardware technologies. Significant progress has been made in the field of artificial intelligence in recent years and is now widely used in healthcare to automate a variety of tasks, which require a high degree of accuracy and precision. The creation of machine learning algorithms, which can learn from data and make predictions based on that learning, has made it possible to use AI in healthcare. Neural networks are used in deep learning, a subfield of machine learning, to simulate how the human brain functions. Crucial advances have been made in clinical decision support, drug discovery, and medical imaging. Furthermore, the rapid development of hardware technologies, such as graphics processing units, has allowed AI systems to process enormous amounts of data quickly and accurately. Due to this, AI-based tools and platforms can help healthcare professionals with tasks such as patient monitoring, disease diagnosis, and treatment planning.","PeriodicalId":15286,"journal":{"name":"Journal of Cellular Biotechnology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cellular Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jcb-230118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 1
Abstract
Artificial intelligence (AI) is a computer’s capacity to carry out operations like speech and image recognition and decision-making that ordinarily require human intelligence. Healthcare is using AI to automate tasks such as medical image analysis and diagnosis that require high precision and accuracy. The healthcare industry is significantly impacted by the rapid development of machine learning algorithms, which are frequently implemented using deep learning, as well as the growth of digital data and computing power supported by improvements in hardware technologies. Significant progress has been made in the field of artificial intelligence in recent years and is now widely used in healthcare to automate a variety of tasks, which require a high degree of accuracy and precision. The creation of machine learning algorithms, which can learn from data and make predictions based on that learning, has made it possible to use AI in healthcare. Neural networks are used in deep learning, a subfield of machine learning, to simulate how the human brain functions. Crucial advances have been made in clinical decision support, drug discovery, and medical imaging. Furthermore, the rapid development of hardware technologies, such as graphics processing units, has allowed AI systems to process enormous amounts of data quickly and accurately. Due to this, AI-based tools and platforms can help healthcare professionals with tasks such as patient monitoring, disease diagnosis, and treatment planning.