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B.N. Pandey, N. Singh
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AI-based imaging biomarker in mammography for prediction of tumor invasiveness
10.1200/jco.2021.39.15_suppl.1568 · doi-reference
Artificial intelligence in liver diseases: improving diagnostics, prognostics and response prediction
10.1016/j.jhepr.2022.100443 · doi-reference
Predicting cancer outcomes from histology and genomics using convolutional networks
10.1073/pnas.1717139115 · doi-reference
Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery
10.3233/cbm-210301 · doi-reference
International evaluation of an AI system for breast cancer screening
10.1038/s41586-019-1799-6 · doi-reference
Predicting patients’ responses to psychotherapy: are some more predictable than others?
10.1037/0022-006x.67.5.698 · doi-reference
Artificial intelligence for clinical oncology
10.1016/j.ccell.2021.04.002 · doi-reference
Asthma and chronic obstructive pulmonary disease (COPD) prediction using PEEP expiratory occlusion data: a hybrid approach with random forest and feedforward neural network
10.1109/ispcc66872.2025.11039525 · doi-reference
Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks
10.1016/j.gie.2018.07.037 · doi-reference
Machine learning in medicine
10.1056/nejmra1814259 · doi-reference
Application of artificial intelligence technology in oncology: towards the establishment of precision medicine
10.3390/cancers12123532 · doi-reference
SD-CNN: a shallow-deep CNN for improved breast cancer diagnosis
10.1016/j.compmedimag.2018.09.004 · doi-reference
The potential applications of artificial intelligence in drug discovery and development
10.33549/physiolres.934765 · doi-reference
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · doi-reference
Artificial intelligence in cancer research, diagnosis and therapy
10.1038/s41568-021-00399-1 · doi-reference
AI and precision oncology in clinical cancer genomics: from prevention to targeted cancer therapies-an outcomes based patient care
10.1016/j.imu.2022.100965 · doi-reference
Artificial intelligence (AI) and big data in cancer and precision oncology
10.1016/j.csbj.2020.08.019 · doi-reference
Clinically applicable deep learning for diagnosis and referral in retinal disease
10.1038/s41591-018-0107-6 · doi-reference
Cancer diagnosis in histopathological image: CNN based approach
10.1016/j.imu.2019.100231 · doi-reference
Accurate and reproducible invasive breast cancer detection in whole-slide images: a deep learning approach for quantifying tumor extent
10.1038/srep46450 · doi-reference
Deep learning–based multi-omics integration robustly predicts survival in liver cancer
10.1158/1078-0432.ccr-17-0853 · doi-reference
OpenGDC: unifying, modeling, integrating cancer genomic data and clinical metadata
10.3390/app10186367 · doi-reference
Detection of cancer in lung with K-NN classification using genetic algorithm
10.1016/j.mspro.2015.06.077 · doi-reference
Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology
10.1038/s41571-019-0252-y · doi-reference
A combined deep CNN: LSTM with a random forest approach for breast cancer diagnosis
10.1155/2022/9299621 · doi-reference
Factors predicting response to treatment in rheumatoid arthritis: the importance of disease duration
10.1002/1529-0131(200001)43:1<22::aid-anr4>3.0.co;2-9 · doi-reference
Diagnosis of lung cancer based on CT scans using CNN
10.1088/1757-899x/928/2/022035 · doi-reference