Explainable AI in Healthcare
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Explainable AI in Healthcare
Unboxing Machine Learning for Biomedicine
Kaya, Tolga; Roy, Mohendra; Raval, Mehul S; Kapdi, Rupal
Taylor & Francis Ltd
04/2025
304
Mole
9781032367125
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1. Human-AI Relationship in Healthcare. 2. Deep Learning in Medical Image Analysis: Recent Models and Explainability. 3. An Overview of Functional Near-Infrared Spectroscopy and Explainable Artificial Intelligence in fNIRS. 4. An Explainable Method for Image Registration with Applications in Medical Imaging. 5. State-of-the-Art Deep Learning Method and Its Explainability for Computerized Tomography Image Segmentation. 6. Interpretability of Segmentation and Overall Survival for Brain Tumors. 7. Identification of MR Image Biomarkers in Brain Tumor Patients Using Machine Learning and Radiomics Features. 8. Explainable Artificial Intelligence in Breast Cancer Identification. 9. Interpretability of Self-Supervised Learning for Breast Cancer Image Analysis. 10. Predictive Analytics in Hospital Readmission for Diabetes Risk Patients. 11. Continuous Blood Glucose Monitoring Using Explainable AI Techniques. 12. Decision Support System for Facial Emotion-Based Progression Detection of Parkinson's Patients. 13. Interpretable Machine Learning in Athletics for Injury Risk Prediction. 14. Federated Learning and Explainable AI in Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI;ACL Injury;DNN Model;Saliency Map;Dl Model;Convolutional Layer;Ml Model;Ai Model;PDPs.;Tomographic View;Black Box Model;fNIRS Data;T1 Mri;Injury Risk Prediction;Cgm Data;fNIRS Studies;Retinal Fundus Images;Glioma Types;Dl Method;Readmission Probability;MR Image Biomarker;Random Forest Classifier;HRCT Image;Mri Dataset;PD Patient;Medical Image Analysis
1. Human-AI Relationship in Healthcare. 2. Deep Learning in Medical Image Analysis: Recent Models and Explainability. 3. An Overview of Functional Near-Infrared Spectroscopy and Explainable Artificial Intelligence in fNIRS. 4. An Explainable Method for Image Registration with Applications in Medical Imaging. 5. State-of-the-Art Deep Learning Method and Its Explainability for Computerized Tomography Image Segmentation. 6. Interpretability of Segmentation and Overall Survival for Brain Tumors. 7. Identification of MR Image Biomarkers in Brain Tumor Patients Using Machine Learning and Radiomics Features. 8. Explainable Artificial Intelligence in Breast Cancer Identification. 9. Interpretability of Self-Supervised Learning for Breast Cancer Image Analysis. 10. Predictive Analytics in Hospital Readmission for Diabetes Risk Patients. 11. Continuous Blood Glucose Monitoring Using Explainable AI Techniques. 12. Decision Support System for Facial Emotion-Based Progression Detection of Parkinson's Patients. 13. Interpretable Machine Learning in Athletics for Injury Risk Prediction. 14. Federated Learning and Explainable AI in Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI;ACL Injury;DNN Model;Saliency Map;Dl Model;Convolutional Layer;Ml Model;Ai Model;PDPs.;Tomographic View;Black Box Model;fNIRS Data;T1 Mri;Injury Risk Prediction;Cgm Data;fNIRS Studies;Retinal Fundus Images;Glioma Types;Dl Method;Readmission Probability;MR Image Biomarker;Random Forest Classifier;HRCT Image;Mri Dataset;PD Patient;Medical Image Analysis
