AIMC Topic: Female

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Comparison of clinical outcomes and accuracy of electrode placement between robot-assisted and conventional deep brain stimulation of the subthalamic nucleus: a single-center study.

Acta neurochirurgica Mar 2, 2021
BACKGROUND: Several surgical methods are used for deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD). This study aimed to compare clinical outcomes and electrode placement accuracy after robot-assisted (RAS) ver...
Electrodes Deep Brain Stimulation Postoperative Period Motor Activity Subthalamic Nucleus Quality of Life Treatment Outcome Magnetic Resonance Imaging Parkinson Disease Robotics Humans Female Male Middle Aged
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Machine learning-based prediction model using clinico-pathologic factors for papillary thyroid carcinoma recurrence.

Scientific reports Mar 2, 2021
This study analyzed the prognostic significance of clinico-pathologic factors, including the number of metastatic lymph nodes (LNs) and lymph node ratio (LNR), in patients with papillary thyroid carcinoma (PTC), and attempted to construct a disease r...
Neoplasm Recurrence, Local Thyroid Cancer, Papillary Decision Making, Computer-Assisted Retrospective Studies Female Aged Adult Male Middle Aged Adolescent Thyroid Neoplasms Lymphatic Metastasis Models, Biological Humans Machine Learning
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Prediction of newborn's body mass index using nationwide multicenter ultrasound data: a machine-learning study.

BMC pregnancy and childbirth Mar 2, 2021
BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.
Neural Networks, Computer Machine Learning Prognosis Retrospective Studies Republic of Korea Humans Body Mass Index Predictive Value of Tests Birth Weight Gestational Age Pregnancy Trimester, Third Pregnancy Female Infant, Newborn Adult Ultrasonography, Prenatal Delivery, Obstetric Body Size Prenatal Diagnosis Fetal Weight
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Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states.

BMC anesthesiology Mar 2, 2021
BACKGROUND: Estimating the depth of anaesthesia (DoA) is critical in modern anaesthetic practice. Multiple DoA monitors based on electroencephalograms (EEGs) have been widely used for DoA monitoring; however, these monitors may be inaccurate under ce...
Middle Aged Electrocardiography Support Vector Machine Decision Trees Heart Rate Anesthesia Humans Neural Networks, Computer Female Reproducibility of Results Male
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Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study.

Journal of medical Internet research Mar 2, 2021
BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences f...
Female SARS-CoV-2 Adult Male Propensity Score Humans Artificial Intelligence Pandemics COVID-19 Research Design
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Machine Learning in Preoperative Prediction of Postoperative Immediate Remission of Histology-Positive Cushing's Disease.

Frontiers in endocrinology Mar 2, 2021
BACKGROUND: There are no established accurate models that use machine learning (ML) methods to preoperatively predict immediate remission after transsphenoidal surgery (TSS) in patients diagnosed with histology-positive Cushing's disease (CD).
Reproducibility of Results Adult Male Middle Aged Diagnosis, Computer-Assisted Humans ROC Curve Pituitary ACTH Hypersecretion Machine Learning Algorithms Pituitary Neoplasms Computer Simulation Predictive Value of Tests Retrospective Studies Area Under Curve Female Remission Induction
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Prediction of Sepsis in COVID-19 Using Laboratory Indicators.

Frontiers in cellular and infection microbiology Mar 2, 2021
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients' condition. We...
Adult Retrospective Studies Male Humans Female ROC Curve Machine Learning Middle Aged SARS-CoV-2 Logistic Models COVID-19 China Risk Factors COVID-19 Testing Prognosis Sepsis Aged
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Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications.

JAMA network open Mar 1, 2021
IMPORTANCE: Postoperative complications can significantly impact perioperative care management and planning.
Follow-Up Studies Intraoperative Period Preoperative Period Postoperative Complications Incidence ROC Curve Decision Support Systems, Clinical United States Risk Factors Male Middle Aged Risk Assessment Humans Machine Learning Retrospective Studies Female
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Assessment of an Exhaled Breath Test Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Lung Cancer.

JAMA network open Mar 1, 2021
IMPORTANCE: Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.
Humans Algorithms Retrospective Studies Female Reproducibility of Results Male Middle Aged Early Detection of Cancer Lung Neoplasms Breath Tests Exhalation Support Vector Machine Follow-Up Studies Mass Spectrometry
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Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients.

JAMA network open Mar 1, 2021
IMPORTANCE: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve compariso...
Infant Adolescent Child, Preschool Child Anti-Bacterial Agents Follow-Up Studies Retrospective Studies Inpatients Electronic Health Records Antimicrobial Stewardship Female Humans Aged Machine Learning Young Adult Adult Male Middle Aged Risk Assessment
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