Название: Concepts of Artificial Intelligence and its Application in Modern Healthcare SystemsАвтор: Deepshikha Agarwal, Khushboo Tripathi, Kumar Krishen
Издательство: CRC Press
Год: 2024
Страниц: 325
Язык: английский
Формат: pdf (true)
Размер: 32.1 MB
This reference text presents the usage of Artificial Intelligence (AI) in healthcare and discusses the challenges and solutions of using advanced techniques like wearable technologies and image processing in the sector.
Machine Learning is the ability of machines or computers to learn without being programmed. It uses numerous algorithms to analyze and evaluate data, and, after analyzing the data, learn from it, and then make judgments or deliver an output. In the field of medical imaging, conventional Machine Learning methods have been applied more recently. With rapidly enhancing computational capacity, along with the readiness of massive volumes of clinical data, traditional Machine Learning (statistical tools based) has been replaced by the neural network-based Deep Learning. Too many complex patterns can be trained, learned, and acquired by Deep Learning compared to traditional Machine Learning systems. Therefore, Machine Learning algorithms permit systems to execute a task by training the machines by applying accessible data to inputs. On the other hand, Deep Learning is a subset of Machine Learning, which is based on biological neural network-learning representations for solving complex problems as humans do.
Features:
Focuses on the use of Artificial Intelligence (AI) in healthcare with issues, applications, and prospects
Presents the application of artificial intelligence in medical imaging, fractionalization of early lung tumour detection using a low intricacy approach, etc.
Discusses an Artificial Intelligence perspective on wearable technology
Analyses cardiac dynamics and assessment of arrhythmia by classifying heartbeat using electrocardiogram (ECG)
Elaborates Machine Learning models for early diagnosis of depressive mental affliction
This book serves as a reference for students and researchers analyzing healthcare data. It can also be used by graduate and post graduate students as an elective course.
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