AIMC Topic: Middle Aged

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A Questionnaire-Based Ensemble Learning Model to Predict the Diagnosis of Vertigo: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Questionnaires have been used in the past 2 decades to predict the diagnosis of vertigo and assist clinical decision-making. A questionnaire-based machine learning model is expected to improve the efficiency of diagnosis of vestibular dis...

Application of artificial intelligence techniques for automated detection of myocardial infarction: a review.

Physiological measurement
Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals worldwide. To diagnose MI, clinicians need to interpret electrocardiog...

Single-port robot-assisted retroperitoneal surgery: A feasible approach.

Actas urologicas espanolas
INTRODUCTION: The concept of surgery through a single incision has been pursued in the field of minimal invasion for the treatment of different pathologies. This, added to a retroperitoneal approach, implies less aggression for the patient at differe...

Development of a machine learning-based risk prediction model for cerebral infarction and comparison with nomogram model.

Journal of affective disorders
BACKGROUND: Development of a cerebral infarction (CI) risk prediction model by mining routine test big data with machine learning algorithms.

Multimodal Neuroelectrophysiological Monitoring Combined with Robot-Assisted Placement of a Transiliac-Transsacral Screw for the Treatment of Transforaminal Sacral Fractures.

BioMed research international
OBJECTIVE: This study aimed to evaluate the safety and efficacy of the fixation of transforaminal sacral fractures using TiRobot-assisted transiliac-transsacral (TITS) screws under multimodal neuroelectrophysiological monitoring (MNM).

Effectiveness of temporal subtraction computed tomography images using deep learning in detecting vertebral bone metastases.

European journal of radiology
PURPOSE: To assess the clinical effectiveness of temporal subtraction computed tomography (TS CT) using deep learning to improve vertebral bone metastasis detection.

Successful Use of a 5G-Based Robot-Assisted Remote Ultrasound System in a Care Center for Disabled Patients in Rural China.

Frontiers in public health
BACKGROUND: Disability has become a global population health challenge. Due to difficulties in self-care or independent living, patients with disability mainly live in community-based care centers or institutions for long-term care. Nonetheless, thes...

Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Theranostics
Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected acute ischemic stroke (AIS), it cannot detect significant changes in the early infarction. We aimed to develop a deep-learning model to identify early ...

External validation of the deep learning system "SpineNet" for grading radiological features of degeneration on MRIs of the lumbar spine.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
BACKGROUND: Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accura...