Development of prognostic model for preterm birth using machine learning in a population-based cohort of Western Australia births between 1980 and 2015.
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DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma.
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Machine learning applied to MRI evaluation for the detection of lymph node metastasis in patients with locally advanced cervical cancer treated with neoadjuvant chemotherapy.
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Radiomics in Head and Neck Cancer Outcome Predictions.
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Current Applications of Artificial Intelligence to Classify Cervical Lymph Nodes in Patients with Head and Neck Squamous Cell Carcinoma-A Systematic Review.
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Artificial intelligence in lung cancer: current applications and perspectives.
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Radiomics-based machine learning for the diagnosis of lymph node metastases in patients with head and neck cancer: Systematic review.
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A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules.
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Radiomics for differentiation of the posterior fossa pilocytic astrocytoma versus hemangioblastomas in adults. A pilot study.
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Differentiation of benign from malignant solid renal lesions using CT-based radiomics and machine learning: comparison with radiologist interpretation.
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Empirical comparison of routinely collected electronic health record data for head and neck cancer-specific survival in machine-learnt prognostic models.
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Value of machine learning algorithms for predicting diabetes risk: A subset analysis from a real-world retrospective cohort study.
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Individualized prediction of chronic kidney disease for the elderly in longevity areas in China: Machine learning approaches.
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Machine learning-based characterization of cuprotosis-related biomarkers and immune infiltration in Parkinson's disease.
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Machine learning-based prediction of disability risk in geriatric patients with hypertension for different time intervals.
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Multimodal ensemble model for Alzheimer's disease conversion prediction from Early Mild Cognitive Impairment subjects.
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Digital Single-Image Smartphone Assessment of Total Body Fat and Abdominal Fat Using Machine Learning.
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Machine Learning Models Predicting Cardiovascular and Renal Outcomes and Mortality in Patients with Hyperkalemia.
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A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson's Disease: Past Studies and Future Perspectives.
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A Machine Learning Model to Predict Length of Stay and Mortality among Diabetes and Hypertension Inpatients.
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Accuracy of Machine Learning Classification Models for the Prediction of Type 2 Diabetes Mellitus: A Systematic Survey and Meta-Analysis Approach.
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Machine Learning Models for Predicting the Risk of Hard-to-Heal Diabetic Foot Ulcers in a Chinese Population.
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Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills.
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Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.
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Using machine-learning strategies to solve psychometric problems.
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Patient-specific quality assurance prediction models based on machine learning for novel dual-layer MLC linac.
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Assessment of Radiology Artificial Intelligence Software: A Validation and Evaluation Framework.
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Using machine learning to investigate earning capacity in patients undergoing psychosomatic rehabilitation-A retrospective health data analysis.
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Factors influencing clinicians' willingness to use an AI-based clinical decision support system.
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Using Machine Learning to Explore the Crucial Factors of Assistive Technology Assessments: Cases of Wheelchairs.
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Occupational Injury Risk Mitigation: Machine Learning Approach and Feature Optimization for Smart Workplace Surveillance.
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Use of convolutional neural networks in skin lesion analysis using real world image and non-image data.
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Real-world data mining meets clinical practice: Research challenges and perspective.
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Influence of nurses in the implementation of artificial intelligence in health care: a scoping review.
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Personalized Prediction of Response to Smartphone-Delivered Meditation Training: Randomized Controlled Trial.
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Understanding the Digital Disruption of Health Care: An Ethnographic Study of Real-Time Multidisciplinary Clinical Behavior in a New Digital Hospital.
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Internet of Things, Machine Learning, and Blockchain Technology: Emerging technologies revolutionizing Universal Health Coverage.
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Artificial intelligence enabled ECG screening for left ventricular systolic dysfunction: a systematic review.
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Performance of a Convolutional Neural Network Derived from PPG Signal in Classifying Sleep Stages.
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Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy.
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Implementation of an All-Day Artificial Intelligence-Based Triage System to Accelerate Door-to-Balloon Times.
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Predicting Acute Onset of Heart Failure Complicating Acute Coronary Syndrome: an Explainable Machine Learning Approach.
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CMB-HUNT: Automatic detection of cerebral microbleeds using a deep neural network.
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A Machine Learning Approach for Detecting Idiopathic REM Sleep Behavior Disorder.
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eXplainable AI allows predicting upper limb rehabilitation outcomes in sub-acute stroke patients.
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The Use of Machine Learning for the Care of Hypertension and Heart Failure.
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Prediction of Intracranial Hypertension and Brain Tissue Hypoxia Utilizing High-Resolution Data from the BOOST-II Clinical Trial.
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Systematic review of artificial intelligence tack in preventive orthopaedics: is the land coming soon?
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Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD.
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A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.
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The Athlete's Heart and Machine Learning: A Review of Current Implementations and Gaps for Future Research.
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Evaluating the Performance of Deep Learning Frameworks for Malaria Parasite Detection Using Microscopic Images of Peripheral Blood Smears.
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Modeling and Forecasting Monkeypox Cases Using Stochastic Models.
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Evaluation of an AI-Based TB AFB Smear Screening System for Laboratory Diagnosis on Routine Practice.
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RU-Net: An improved U-Net placenta segmentation network based on ResNet.
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Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.
Hu Tingting et al. Scientific reports 2022 12(1) 19063