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This book explores the impact and significance of big data in clinical and medical settings. It delves into the opportunities and limitations of large datasets, including their application in national health databases and electronic health records. The text discusses best practices for interpreting big data, the biases and ethical implications involved, and the integration of artificial intelligence in healthcare. It highlights the importance of patient perspectives on data privacy and trust, with a focus on improving patient outcomes and advancing research. The book is intended for healthcare professionals, researchers, and policymakers interested in leveraging big data to enhance clinical practices. -- Publisher's description.

Big data. --- Medical informatics. --- Otorhinolaryngologic Diseases. --- Medical Informatics Applications. --- Medical Informatics. --- Otolaryngology ǂx Data processing. --- Otolaryngology --- Otorhinolaryngologic Diseases --- Medical Informatics Applications --- Medical Informatics --- methods --- Data processing. --- methods.

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The effective and efficient management of healthcare institutions is key to the successful development of national health systems. In an increasingly digital society, the skills involved in health information management become a primary factor in ensuring this development. Employment is projected to grow in all areas of healthcare, but especially in those related to information management, such as applied informatics, public health informatics and medical informatics. This book, 'Health Information Management: Empowering Public Health', aims to provide a clear and comprehensive introduction to the study and development of health information management. It is designed for use by university and vocational courses to train allied health professionals. It can also be used as an in-service training tool for new healthcare-facility personnel, for those working in government healthcare institutions, independent billing and health assurance services, or individually by health information specialists. The book describes health information management, and explains how it merges the fields of health care and information technology. Readers will learn logical thinking and communication, and will be introduced to the organizational processes in healthcare institutions, as well as finding out how to organize and analyze health care data; accurately record, store and assess health data; use an electronic patient record system; and provide statistical analysis and interpret the results.--

Medical informatics. --- Public Health Informatics --- Medical Informatics Applications --- Médecine --- Informatique.

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Medical informatics --- Medicine --- Medical Informatics Applications --- Médecine --- Data processing --- Informatique --- Informatique.

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Computational Methods and Deep Learning for Ophthalmology presents readers with the concepts and methods needed to design and use advanced computer-aided diagnosis systems for ophthalmologic abnormalities in the human eye. Chapters cover computational approaches for diagnosis and assessment of a variety of ophthalmologic abnormalities. Computational approaches include topics such as Deep Convolutional Neural Networks, Generative Adversarial Networks, Auto Encoders, Recurrent Neural Networks, and modified/hybrid Artificial Neural Networks. Ophthalmological abnormalities covered include Glaucoma, Diabetic Retinopathy, Macular Degeneration, Retinal Vein Occlusions, eye lesions, cataracts, and optical nerve disorders.

Deep learning (Machine learning) --- Ophthalmology --- Medicine --- Eye --- Learning, Deep (Machine learning) --- Iterative methods (Mathematics) --- Machine learning --- Data processing. --- Diseases --- Deep Learning --- Medical Informatics Applications --- Medical Informatics Computing --- Eye Diseases --- Diagnosis --- diagnosis --- Deep Learning. --- Medical Informatics Applications. --- Medical Informatics Computing. --- diagnosis.

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One-liner (250 characters, including spaces): Examines interventions in the healthcare system that use Electronic Medical Record Systems (EMR-S) to affect patient trajectories--i.e., the sequence of encounters a patient has with the healthcare system.

Cost-Benefit Analysis. --- Health maintenance organization patients. --- Medical Informatics Applications. --- Technology Assessment, Biomedical --- Health maintenance organizations --- Patients