Disruptive Trends in Computer Aided Diagnosis
portes grátis
Disruptive Trends in Computer Aided Diagnosis
Das, Rik; Bhattacharyya, Siddhartha; Nandy, Sudarshan
Taylor & Francis Ltd
09/2021
196
Dura
Inglês
9780367493370
15 a 20 dias
560
Descrição não disponível.
1. Evolution of Computer Aided Diagnosis: The Inception and Progress
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Computer Aided Diagnosis;Machine Learning;Corona Virus;Diagnosis;Support Vector Machines;Neural Network;ARIMA Model;HRV;HRV Parameter;Computer Aided;Cad;HF Band Power;HRV Analysis;HRV Index;Error Back Propagation Algorithm;Fiducial Points;Ann Classifier;RIC;Symptomatic Pad;Coronary Heart Attack;MERS;Deep Learning Methods;Chest X-ray Images;Missing Values;Semantic Imaging;Diabetic Subjects;SD Ratio;Non-hypertensive Subjects
1. Evolution of Computer Aided Diagnosis: The Inception and Progress
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Computer Aided Diagnosis;Machine Learning;Corona Virus;Diagnosis;Support Vector Machines;Neural Network;ARIMA Model;HRV;HRV Parameter;Computer Aided;Cad;HF Band Power;HRV Analysis;HRV Index;Error Back Propagation Algorithm;Fiducial Points;Ann Classifier;RIC;Symptomatic Pad;Coronary Heart Attack;MERS;Deep Learning Methods;Chest X-ray Images;Missing Values;Semantic Imaging;Diabetic Subjects;SD Ratio;Non-hypertensive Subjects
