Explore
Artificial Intelligence in Healthcare: Current State and Future Perspectives
Tim Hulsen (editor)
2024
0 Ungluers have
Faved this Work
Login to Fave
Artificial intelligence (AI), which is the simulation of human intelligence processes by machines, is having a growing impact on healthcare. Via AI, researchers can provide new approaches to merge, analyze, and process complex “big data” and gain more actionable insights, understanding, and knowledge at an individual and population level. Medical staff can be helped by AI-assisted clinical decision support (CDS), i.e., machine learning (ML) and deep learning (DL) models that analyze large medical datasets. They do this by summarizing radiology and pathology reports by means of natural language processing (NLP), automating repetitive but time-consuming tasks, and much more. Patients can talk to chatbots who have access to all medical knowledge in the world, including the patient’s medical history, and provide personalized advice. This Special Issue intends to show some examples of how AI impacts healthcare, with some discussion on potential future developments as well as challenges. Since this Special Issue contains papers from 2023 and 2024, the era of Generative AI (GenAI), naturally there are papers related to ChatGPT and chatbots. There are also papers on prediction modeling in primary care, polychronic conditions, and heart disease. Other papers focus on the classification of colon cancer and Alzheimer’s disease. Finally, this Special Issue also includes papers on orthodontic diagnosis and treatment planning, anxiety treatment, and explainable AI (XAI).
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 8 times via unglue.it ebook links.
- 8 - pdf (CC BY-NC-ND) at Unglue.it.
Keywords
- 3D printing
- AI
- Alzheimer’s disease
- artificial intelligence
- AutoGluon
- AutoKeras
- AutoML
- big data
- binaural beats
- Cardiovascular Disease
- care management interventions
- CBCT
- chatbot
- ChatGPT
- colon cancer
- convolutional neural networks
- coronary artery disease
- Data science
- dataset
- decision support system design and evaluation
- deep convolutional neural network
- deep learning
- Diagnosis
- EEG signals
- explainability
- explainable
- face scan
- facial analysis
- flower pollination optimization algorithm
- graph convolutional networks
- Healthcare
- heart disease
- histological diagnosis
- Histology
- image classification
- Internet of Things
- Machine learning
- medicine
- n/a
- Natural Language Processing
- Pathology
- patient care outcomes and modeling
- polychronic conditions
- prediction
- Predictive analytics
- primary care
- PyCaret
- Radiotherapy
- thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine
- transfer learning
- transformer networks
- treatment evaluation
- treatment planning
- wavelet transform
- XAI
Links
DOI: 10.3390/books978-3-7258-1083-3Editions