OBJECTIVE: Multiple studies in the past have developed equations to determine the ideal lumbar lordosis (ILL) in the sagittal plane. These equations differ but all look to accomplish the same goal of providing the surgeon with specific alignment targ...
OBJECTIVE: Software engineering innovations have led to the development of virtual surgical planning software (VSPS) for deformity correction. VSPS uses calibrated radiographs and machine learning predictive models to simulate postoperative spinopelv...
OBJECTIVE: The aim of this study was to develop and compare 4 predictive algorithms, including logistic regression (LR), random forest (RF), gradient boosting machine (GBM), and neural network (NN), for perioperative outcomes in adult spinal deformit...
BACKGROUND: Machine-learning models directly predicting iron biomarkers after blood donation could help to manage donation-associated iron deficiency and avoid low haemoglobin deferrals. No such models have been externally validated internationally. ...
International journal of geriatric psychiatry
Jun 1, 2025
OBJECTIVES: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists. This study aimed to differentiate elderly treatment-resistant depression (TRD) comorbid with parkin...
PURPOSE: In India, 4.80 million people are blind, and 4.69 million have severe visual impairment. Globally, the digital era and the advent of artificial intelligence devices offer solutions for daily challenges faced by the visually impaired, but the...
OBJECTIVES: Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). This study aimed to develop a machine learning (ML) model that predicts the need for such interventi...
There is an urgent need for the precise prediction of cerebral amyloidosis using noninvasive and accessible indicators to facilitate the early diagnosis of individuals with the preclinical stage of Alzheimer's disease (AD). Two hundred and four indiv...
BACKGROUND/AIM: Optimal antimicrobial selection for patients with febrile neutropenia (FN) may differ depending on the underlying mechanisms. We aimed to develop a model for predicting the severity of bacteremia in patients with FN and hematologic ma...
BACKGROUND/AIM: This study aimed to evaluate the diagnostic accuracy (DA) of four artificial intelligence (AI) models compared to logistic regression (LR) in enhancing the performance of the fecal immunochemical test (FIT) for the detection of colore...
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