Prediction of low Apgar score at five minutes following labor induction intervention in vaginal deliveries: machine learning approach for imbalanced data at a tertiary hospital in North Tanzania.
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The role of artificial intelligence in paediatric neuroradiology.
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Refinement and Validation of a Clinical-Based Approach to Evaluate Young Febrile Infants.
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The principles of whole-hospital predictive analytics monitoring for clinical medicine originated in the neonatal ICU.
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Development and validation of clinical prediction models for breast cancer incidence and mortality: a protocol for a dual cohort study.
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Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study.
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Discrimination of Breast Cancer Based on Ultrasound Images and Convolutional Neural Network.
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Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.
Yuan Luo et al. Journal of X-ray science and technology 2022

Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram.
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Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment.
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The Value of Artificial Intelligence Film Reading System Based on Deep Learning in the Diagnosis of Non-Small-Cell Lung Cancer and the Significance of Efficacy Monitoring: A Retrospective, Clinical, Nonrandomized, Controlled Study.
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Evaluation and Monitoring of Endometrial Cancer Based on Magnetic Resonance Imaging Features of Deep Learning.
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Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches.
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Evaluation of Deep Learning-Based Automated Detection of Primary Spine Tumors on MRI Using the Turing Test.
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Developing an algorithm across integrated healthcare systems to identify a history of cancer using electronic medical records.
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Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.
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Artificial Intelligence for Survival Prediction in Brain Tumors on Neuroimaging.
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Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review.
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A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study.
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Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.
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Identification of subjective cognitive decline due to Alzheimer's disease using multimodal MRI combining with machine learning.
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Predicting diagnosis 4 years prior to Alzheimer's disease incident.
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Harnessing Big Data, Smart and Digital Technologies and Artificial Intelligence for Preventing, Early Intercepting, Managing, and Treating Psoriatic Arthritis: Insights From a Systematic Review of the Literature.
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Artificial intelligence for medical image analysis in epilepsy.
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Predicting Falls in Long-term Care Facilities: Machine Learning Study.
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Applications of Artificial Intelligence in Myopia: Current and Future Directions.
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LONGL-Net: temporal correlation structure guided deep learning model to predict longitudinal age-related macular degeneration severity.
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How Machine Learning is Powering Neuroimaging to Improve Brain Health.
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Predictive capacity of four machine learning models for in-hospital postoperative outcomes following total knee arthroplasty.
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Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study.
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Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder.
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The future of artificial intelligence in medicine: Medical-legal considerations for health leaders.
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The Future Ethics of Artificial Intelligence in Medicine: Making Sense of Collaborative Models.
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Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility?
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Predicting hospitalisations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study.
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Five points to consider when reading a translational machine-learning paper.
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The potential of precision psychiatry: what is in reach?
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Artificial intelligence in perioperative medicine - a narrative review.
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Development and validation of early prediction models for new-onset functional impairment at hospital discharge of ICU admission.
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Artificial intelligence and multidisciplinary team meetings; a communication challenge for radiologists' sense of agency and position as spider in a web?
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Predicting non-response to multimodal day clinic treatment in severely impaired depressed patients: a machine learning approach.
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Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study.
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A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare.
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Multimedia Data-Based Mobile Applications for Dietary Assessment.
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Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis.
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Artificial intelligence for caries and periapical periodontitis detection.
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Practical Machine Learning Model to Predict the Recovery of Motor Function in Patients with Stroke.
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Usability of Smart Home Thermostat to Evaluate the Impact of Weekdays and Seasons on Sleep Patterns and Indoor Stay: Observational Study.
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Prediction of Recurrent Ischemic Stroke Using Registry Data and Machine Learning Methods: The Erlangen Stroke Registry.
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A Systematic Review and Bibliometric Analysis of Applications of Artificial Intelligence and Machine Learning in Vascular Surgery.
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A Collaborative Approach for the Development and Application of Machine Learning Solutions for CMR-Based Cardiac Disease Classification.
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Machine learning in the detection and management of atrial fibrillation.
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Incident and recurrent myocardial infarction (MI) in relation to comorbidities: Prediction of outcomes using machine learning algorithms.
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Identification of Incident Atrial Fibrillation From Electronic Medical Records.
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Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure.
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Machine Learning in Cardiovascular Imaging.
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[Artificial intelligence-based literature data warehouse for vaccine safety].
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Predicting the impact of climate change on the re-emergence of malaria cases in China using LSTMSeq2Seq deep learning model: a modelling and prediction analysis study.
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The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality.
Ming Damien K et al. Frontiers in digital health 2022 4849641

Sepsis Prediction for the General Ward Setting.
Yu Sean C et al. Frontiers in digital health 2022 4848599

A Doubly Robust Machine Learning-Based Approach to Evaluate Body Mass Index as a Modifier of the Association Between Fruit and Vegetable Intake and Preeclampsia.
Bodnar Lisa M et al. American journal of epidemiology 2022