Explainable AI in Healthcare and Medicine: Building a Culture of Transparency and Accountability
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- Artikel-Nr.: 10422908
Beschreibung
Explainability and Interpretability: Keys to Deep Medicine.- Fast Similar Patient Retrieval from Large Scale Healthcare Data: A Deep Learning-based Binary Hashing Approach.- A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs.- Machine learning discrimination of Parkinson's Disease stages from walk-er-mounted sensors data.- Personalized Dual-Hormone Control for Type 1 Diabetes Using Deep Rein-forcement Learning.- A Generalizable Method for Automated Quality Control of Functional Neuroimaging Datasets.- Uncertainty Characterization for Predictive Analytics with Clinical Time Series Data.- A Dynamic Deep Neural Network for Multimodal Clinical Data Analysis.- DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data.- A Deep Learning Approach for Classifying Nonalcoholic Steatohepatitis Pa-tients from Nonalcoholic Fatty Liver Disease Patients using Electronic Medical Records.
Eigenschaften
Breite: | 163 |
Gewicht: | 688 g |
Höhe: | 26 |
Länge: | 244 |
Seiten: | 344 |
Sprachen: | Englisch |
Autor: | Arash Shaban-Nejad, David L. Buckeridge, Martin Michalowski |
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