Før Memmo var notatene mine spredt overalt i PDF-er. Nå samler et arbeidsområde alt på ett sted – jeg ser akkurat hva som gjenstår å studere.
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis.
The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images.
This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector.
Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India.
Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India.
Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Før Memmo var notatene mine spredt overalt i PDF-er. Nå samler et arbeidsområde alt på ett sted – jeg ser akkurat hva som gjenstår å studere.
Memmos sammendrag er gull før eksamen. Jeg slipper å lese 800 sider to uker før – bare det viktigste.
AI-chatten har reddet meg kvelden før eksamen mer enn én gang. Jeg bare spør til jeg forstår – slipper å vente på svar i en studiegruppe.
Quizene treffer akkurat det jeg trenger å vite. Memmo holder styr på hva jeg sliter med – så jeg øver bare på det som er verdt det.
Flashcards med repetisjon over tid er magi. Memmo vet når jeg er i ferd med å glemme noe og viser det igjen.
AI-podkastene er min favoritt. Jeg lytter på vei til skolen og får en repetisjon uten å sitte foran en datamaskin.
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