Journal of Artificial Intelligence and Digital Health
ISSN:
3139-6267 (Online)
DOI Prefix (Crossref): 10.67238
Machine Learning and Deep Learning
Machine Learning & Deep Learning in healthcare involve advanced computational models that learn from medical data to identify patterns, make predictions, and support clinical decisions. Machine learning algorithms assist in risk assessment, disease classification, and outcome forecasting. Deep learning, particularly neural networks, enables high-accuracy analysis of medical images, signals, and complex patient records. These technologies help automate diagnostics, detect rare conditions, and personalize treatment recommendations. They enhance drug discovery, genomics research, and real-time monitoring systems. By processing vast datasets with speed and precision, ML and DL are reshaping modern healthcare with more accurate, faster, and data-driven solutions.
Article Processing Timeline
| 2-5 Days | Initial Quality & Plagiarism Check |
| 25-35 Days |
Peer Review Feedback |
| 45-60 Days | Total article processing time |
EDITORIAL & PUBLICATION INFORMATION
| English | Publication Language |
| Single-Blind | Peer-Review Model |
| 17% | Acceptance Rate |
| <18% | Similarity Screening Guideline |
| Open Access | Access Model |
All manuscripts undergo editorial assessment and originality screening as part of the journal's evaluation process. The acceptance rate shown is based on journal-level editorial data and may change over time. Similarity reports are assessed editorially and are not interpreted solely on the basis of a numerical similarity score.
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