Health and Public Health Applications for Decision Support Using Machine Learning
"Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diag...
Zapisane w:
| Format: | Online |
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| Język: | angielski |
| Wydane: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Hasła przedmiotowe: | |
| Dostęp online: | ONIX_20230911_9783036585499_45 |
| Etykiety: |
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| _version_ | 1869514164085456896 |
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| collection | Directory of Open Access Books |
| description | "Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diagnosis, and public health management. The reprint covers a wide range of topics, including natural language processing for biomedical relation extraction, ensemble learning for blood glucose level forecasting in diabetes management, machine learning for predicting walking stability and fall risk among the elderly, deep learning for pneumonia-infected lung volume quantification, and more.The reprint also discusses applications in precision medicine, early detection of renal damage, cardiac health monitoring, stress classification for mental health assessment, and early diagnosis of intracranial internal carotid artery stenosis. It emphasizes the role of machine learning in managing health crises, such as COVID-19 detection using ECG, voice, and X-ray systems, and reviews AI models in diagnosing adult-onset dementia disorders.Overall, this reprint aims to inspire researchers and healthcare professionals by showcasing the transformative potential of machine learning in healthcare. It hopes to encourage further research and collaboration to advance healthcare and technological innovations for a healthier future. |
| format | Online |
| id | doab-20.500.12854ir-113912 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1139122023-09-11T11:59:27Z Health and Public Health Applications for Decision Support Using Machine Learning Rodrigues, Pedro Miguel Lobo Marques, João Alexandre Madeiro, João Paulo do Vale adult-onset dementia Alzheimer’s disease magnetic resonance imaging artificial intelligence machine learning neural networks atherosclerosis Doppler ultrasound internal carotid artery hemodynamic modeling stroke stress emotion action units speech audio visual RNN-LSTM petri-plates colonies machine-learning models discrimination Measurement uncertainty Monte Carlo method ECG Cardiac health COVID-19 signal processing image processing computerized diagnostic systems subclinical renal damage risk assessment tool group-based trajectory modeling screening strategy CVD classification data selection convolutional neural network pretrained model deep learning transfer learning infected lung segmentation quantification of lung disease severity comparison between manual and automated image segmentation deep neural network COVID-19 detection COVID-19 severity assessment gait neuromuscular control movement synergy overground walking principal component analysis (PCA) largest Lyapunov exponent (LyE) time-series forecasting blood glucose diabetes ensemble learning artificial neural network DDI (drug–drug interaction) CPR (chemical–protein relation) transformer self-attention GAT (graph-attention network) relation extraction ChemProt T5 (text-to-text transfer transformer) n/a "Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diagnosis, and public health management. The reprint covers a wide range of topics, including natural language processing for biomedical relation extraction, ensemble learning for blood glucose level forecasting in diabetes management, machine learning for predicting walking stability and fall risk among the elderly, deep learning for pneumonia-infected lung volume quantification, and more.The reprint also discusses applications in precision medicine, early detection of renal damage, cardiac health monitoring, stress classification for mental health assessment, and early diagnosis of intracranial internal carotid artery stenosis. It emphasizes the role of machine learning in managing health crises, such as COVID-19 detection using ECG, voice, and X-ray systems, and reviews AI models in diagnosing adult-onset dementia disorders.Overall, this reprint aims to inspire researchers and healthcare professionals by showcasing the transformative potential of machine learning in healthcare. It hopes to encourage further research and collaboration to advance healthcare and technological innovations for a healthier future. 2023-09-11T11:59:20Z 2023-09-11T11:59:20Z 2023 book ONIX_20230911_9783036585499_45 9783036585499 9783036585482 https://directory.doabooks.org/handle/20.500.12854/113912 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/7753 https://mdpi.com/books/pdfview/book/7753 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-8548-2 10.3390/books978-3-0365-8548-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036585499 9783036585482 214 open access |
| spellingShingle | adult-onset dementia Alzheimer’s disease magnetic resonance imaging artificial intelligence machine learning neural networks atherosclerosis Doppler ultrasound internal carotid artery hemodynamic modeling stroke stress emotion action units speech audio visual RNN-LSTM petri-plates colonies machine-learning models discrimination Measurement uncertainty Monte Carlo method ECG Cardiac health COVID-19 signal processing image processing computerized diagnostic systems subclinical renal damage risk assessment tool group-based trajectory modeling screening strategy CVD classification data selection convolutional neural network pretrained model deep learning transfer learning infected lung segmentation quantification of lung disease severity comparison between manual and automated image segmentation deep neural network COVID-19 detection COVID-19 severity assessment gait neuromuscular control movement synergy overground walking principal component analysis (PCA) largest Lyapunov exponent (LyE) time-series forecasting blood glucose diabetes ensemble learning artificial neural network DDI (drug–drug interaction) CPR (chemical–protein relation) transformer self-attention GAT (graph-attention network) relation extraction ChemProt T5 (text-to-text transfer transformer) n/a Health and Public Health Applications for Decision Support Using Machine Learning |
| title | Health and Public Health Applications for Decision Support Using Machine Learning |
| title_full | Health and Public Health Applications for Decision Support Using Machine Learning |
| title_fullStr | Health and Public Health Applications for Decision Support Using Machine Learning |
| title_full_unstemmed | Health and Public Health Applications for Decision Support Using Machine Learning |
| title_short | Health and Public Health Applications for Decision Support Using Machine Learning |
| title_sort | health and public health applications for decision support using machine learning |
| topic | adult-onset dementia Alzheimer’s disease magnetic resonance imaging artificial intelligence machine learning neural networks atherosclerosis Doppler ultrasound internal carotid artery hemodynamic modeling stroke stress emotion action units speech audio visual RNN-LSTM petri-plates colonies machine-learning models discrimination Measurement uncertainty Monte Carlo method ECG Cardiac health COVID-19 signal processing image processing computerized diagnostic systems subclinical renal damage risk assessment tool group-based trajectory modeling screening strategy CVD classification data selection convolutional neural network pretrained model deep learning transfer learning infected lung segmentation quantification of lung disease severity comparison between manual and automated image segmentation deep neural network COVID-19 detection COVID-19 severity assessment gait neuromuscular control movement synergy overground walking principal component analysis (PCA) largest Lyapunov exponent (LyE) time-series forecasting blood glucose diabetes ensemble learning artificial neural network DDI (drug–drug interaction) CPR (chemical–protein relation) transformer self-attention GAT (graph-attention network) relation extraction ChemProt T5 (text-to-text transfer transformer) n/a |
| topic_facet | adult-onset dementia Alzheimer’s disease magnetic resonance imaging artificial intelligence machine learning neural networks atherosclerosis Doppler ultrasound internal carotid artery hemodynamic modeling stroke stress emotion action units speech audio visual RNN-LSTM petri-plates colonies machine-learning models discrimination Measurement uncertainty Monte Carlo method ECG Cardiac health COVID-19 signal processing image processing computerized diagnostic systems subclinical renal damage risk assessment tool group-based trajectory modeling screening strategy CVD classification data selection convolutional neural network pretrained model deep learning transfer learning infected lung segmentation quantification of lung disease severity comparison between manual and automated image segmentation deep neural network COVID-19 detection COVID-19 severity assessment gait neuromuscular control movement synergy overground walking principal component analysis (PCA) largest Lyapunov exponent (LyE) time-series forecasting blood glucose diabetes ensemble learning artificial neural network DDI (drug–drug interaction) CPR (chemical–protein relation) transformer self-attention GAT (graph-attention network) relation extraction ChemProt T5 (text-to-text transfer transformer) n/a |
| url | ONIX_20230911_9783036585499_45 |