Deep learning-based model detects atrial septal defects from electrocardiography: a cross-sectional multicenter hospital-based study.
Kotaro Miura et al. EClinicalMedicine 2023 63102141

Predicting the drop out from the maternal, newborn and child healthcare continuum in three East African Community countries: application of machine learning models.
Chenai Mlandu et al. BMC Med Inform Decis Mak 2023 23(1) 191

Use of artificial intelligence in the management of T1 colorectal cancer: a new tool in the arsenal or is deep learning out of its depth?
James Weiquan Li et al. Clin Endosc 2023

The diagnostic value of machine learning for the classification of malignant bone tumor: a systematic evaluation and meta-analysis.
Yue Li et al. Front Oncol 2023 131207175

The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule.
Seulgi You et al. Insights Imaging 2023 14(1) 149

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.
Hongzheng Song et al. Cancer Imaging 2023 23(1) 89

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning.
Audrey Shiner et al. Genes (Basel) 2023 14(9)

Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study.
Siyu Cai et al. J Cancer Res Clin Oncol 2023

Predicting Mammogram Screening Follow Through with Electronic Health Record and Geographically Linked Data.
Matthew Davis et al. Cancer Res Commun 2023

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.
Jiping Wang et al. Yale J Biol Med 2023 96(3) 327-346

Enhanced and unenhanced: Radiomics models for discriminating between benign and malignant cystic renal masses on CT images: A multi-center study.
Lesheng Huang et al. PLoS One 2023 18(9) e0292110

Predicting Long-Term Care Service Demands for Cancer Patients: A Machine Learning Approach.
Shuo-Chen Chien et al. Cancers (Basel) 2023 15(18)

Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review.
Arman Ghavidel et al. J Cancer Surviv 2023

Development and testing of a random forest-based machine learning model for predicting events among breast cancer patients with a poor response to neoadjuvant chemotherapy.
Yudi Jin et al. Eur J Med Res 2023 28(1) 394

Deep learning for the early identification of periodontitis: a retrospective, multicentre study.
Q Liu et al. Clin Radiol 2023

Artificial intelligence for telemedicine diabetic retinopathy screening: a review.
Luis Filipe Nakayama et al. Ann Med 2023 55(2) 2258149

Paving the Way for Predicting the Progression of Cognitive Decline: The Potential Role of Machine Learning Algorithms in the Clinical Management of Neurodegenerative Disorders.
Caterina Formica et al. J Pers Med 2023 13(9)

Predicting three-month fasting blood glucose and glycated hemoglobin changes in patients with type 2 diabetes mellitus based on multiple machine learning algorithms.
Xue Tao et al. Sci Rep 2023 13(1) 16437

A multicenter study on the application of artificial intelligence radiological characteristics to predict prognosis after percutaneous nephrolithotomy.
Jian Hou et al. Front Endocrinol (Lausanne) 2023 141184608

Using unsupervised machine learning to predict quality of life after total knee arthroplasty.
J Hunter et al. J Arthroplasty 2023

Deep Learning of Speech Data for Early Detection of Alzheimer's Disease in the Elderly.
Kichan Ahn et al. Bioengineering (Basel) 2023 10(9)

A Deep Learning-Based Model for Classifying Osteoporotic Lumbar Vertebral Fractures on Radiographs: A Retrospective Model Development and Validation Study.
Yohei Ono et al. J Imaging 2023 9(9)

Challenges in mapping European rare disease databases, relevant for ML-based screening technologies in terms of organizational, FAIR and legal principles: scoping review.
Ralitsa Raycheva et al. Front Public Health 2023 111214766

Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records.
Geir Thore Berge et al. BMC Med Inform Decis Mak 2023 23(1) 188

Artificial Intelligence: its Future and Impact on Acute Medicine.
M Schinkel et al. Acute Med 2023 22(3) 150-153

Advancing polytrauma care: developing and validating machine learning models for early mortality prediction.
Wen He et al. J Transl Med 2023 21(1) 664

Revolutionizing healthcare: the role of artificial intelligence in clinical practice.
Shuroug A Alowais et al. BMC Med Educ 2023 23(1) 689

Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses.
Benjamin Bender et al. Eur Radiol 2023

Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications.
Sahar Borna et al. Healthcare (Basel) 2023 11(18)

Centering Public Perceptions on Translating AI Into Clinical Practice: Patient and Public Involvement and Engagement Consultation Focus Group Study.
William Lammons et al. J Med Internet Res 2023 25e49303

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.
Hamed Akhlaghi et al. Emerg Med Australas 2023

The promise of data science for health research in Africa.
Clement A Adebamowo et al. Nat Commun 2023 14(1) 6084

Implementing AI Models for Prognostic Predictions in High-Risk Burn Patients.
Chin-Choon Yeh et al. Diagnostics (Basel) 2023 13(18)

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.
Aitizaz Ali et al. Sensors (Basel) 2023 23(18)

Development of a machine learning algorithm based on administrative claims data for identification of ED anaphylaxis patient visits.
Ronna L Campbell et al. J Allergy Clin Immunol Glob 2023 2(1) 61-68

Text generative artificial intelligence tools for clinical applications: scope and concerns.
Akhilesh Vikram Singh et al. Ir J Med Sci 2023

Prediction model of atrial fibrillation recurrence after Cox-Maze IV procedure in patients with chronic valvular disease and atrial fibrillation based on machine learning algorithm.
Zenan Jiang et al. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2023 48(7) 995-1007

Single-lead arrhythmia detection through machine learning: cross-sectional evaluation of a novel algorithm using real-world data.
Henry Mitchell et al. Open Heart 2023 10(2)

Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging.
Krunoslav Michael Sveric et al. Int J Cardiol 2023 131383

Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients.
Chien Wei Oei et al. Sensors (Basel) 2023 23(18)

Machine learning in precision diabetes care and cardiovascular risk prediction.
Evangelos K Oikonomou et al. Cardiovasc Diabetol 2023 22(1) 259

Prediction of respiratory failure risk in patients with pneumonia in the ICU using ensemble learning models.
Guanqi Lyu et al. PLoS One 2023 18(9) e0291711

Detection of Bacterial Colonization in Lung Transplant Recipients Using an Electronic Nose.
Nynke Wijbenga et al. Transplant Direct 2023 9(10) e1533

Clinical Decision Support System to Detect the Occurrence of Ventilator-Associated Pneumonia in Pediatric Intensive Care.
Jerome Rambaud et al. Diagnostics (Basel) 2023 13(18)

Preoperative Prediction of Postoperative Infections Using Machine Learning and Electronic Health Record Data.
Yaxu Zhuang et al. Ann Surg 2023

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?
Thomas G Day et al. Prenat Diagn 2023