Titlebook: Artificial Intelligence and Machine Learning for Healthcare; Vol. 1: Image and Da Chee-Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain Book 2023 Th

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Classification of Arrhythmia Signals Using Hybrid Convolutional Neural Network (CNN) Model, approach based on long short-term memory (LSTM) approach. Experimental data are obtained from PhysioNet CinC Challenge 2017 database. ECG signals are preprocessed via filtering, QRS detection, segmentation and median wave selection. One-dimensional CNN, hybrid CNN–long short-term memory (CNN–LSTM)

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Polyp Segmentation with Deep Ensembles and Data Augmentation,een loss functions. Our best ensembles are tested on a large dataset composed of samples taken from five polyp benchmarks. Ensembles are assessed and compared with the best method reported in the literature and shown to produce state-of-the-art results. The source code, the dataset, and the testing

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Autistic Verbal Behavior Parameters,of head bouncing and can be extended to some other movements during interactions recorded in diverse circumstances with ASD patients. A short tracking and lightweight processing approach is presented, and applied to a small video test set. Results are validated against manually detected movements. A

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https://doi.org/10.1007/978-3-031-11154-9Artificial Intelligence; Deep Learning; Intelligent Technology; Assistive Technology; Ageing Populations

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eCustomer Relationship Management,wn and commonly used AI algorithms are presented. We continued the chapter with the pros and cons of AI, highlighting the main advantages and disadvantages it has. The chapter finishes with some of the newest real-life applications of AI in different healthcare sectors from diagnostic, drug developm

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