f Emerging Intelligent Computing Techniques and their Applications Using Machine Learning

References

1. KushwahaP.K. DagurA. ShuklaD. HSLE: A hybrid ensemble classifier for prediction of heart diseaseRec. Adv. Elect Electron. Eng.20251820251810.2174/0123520965291887240422051823
   [Google Scholar]
2. LohaniB.P. DagurA. ShuklaD. An efficient approach for diabetes classification using feature selection and hyperparameter tuningRec. Adv. Elect Electron. Eng.20251820251710.2174/0123520965291885240315051751
   [Google Scholar]
3. BhushanIndu ChandraSubhash YadavArvind LearningIntegrating Machine Integrating machine learning and feature extraction for islanding detection in grid-connected photovoltaic systems: a hybrid intelligent approachRec. Adv. Elect Electron. Eng.20251610.2174/0123520965308320240624101404
   [Google Scholar]
4. WangY. WangL. HuangZ. ZhangY. HanY. Multimodal medical image fusion method based on the swin transformer and self-supervised contrast learning.Rec. Adv. Elect Electron. Eng.20251510.2174/0123520965311272240709053422
   [Google Scholar]
5. GaudinM. KaurS. SharmaP. KumarR. A comparative analysis of machine learning models for the classification of heart failure patients in the intensive care unit.Rec. Adv. Elect Electron. Eng.20251810.2174/0123520965312805240506113451
   [Google Scholar]
6. SrivastavaR. PandeyD.R. SinghA.K. Comparative analysis of radiological and machine learning-based interpretations for differentiating COVID-19 and pneumonia.Rec. Adv. Elect Electron. Eng.20251810.2174/0123520965325192240923074336
   [Google Scholar]
7. AgnihotriA. KohliN. Explainable artificial intelligence-based attention guided uncertainty weighting ensemble model for the classification of COVID-19 and pneumonia in X-ray medical images.Rec. Adv. Elect Electron. Eng.202510.2174/0123520965334135241115064754
   [Google Scholar]