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Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.

Surgical endoscopy
BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatment for patients with unresectable malignant biliary obstruction (MBO), which can relieve biliary obstruction and prolong survival. Post-ERCP cholangi...

Predicting the prognosis of radical gastrectomy for patients with locally advanced gastric cancer after neoadjuvant chemotherapy using machine learning technology: a multicenter study in China.

Surgical endoscopy
BACKGROUND: Neoadjuvant chemotherapy (NAC) can improve the prognosis of patients with locally advanced gastric cancer (LAGC). However, precise models for accurate prognostic predictions are lacking. We aimed to utilize Cox regression and integrate va...

Development of a deep learning-based MRI diagnostic model for human Brucella spondylitis.

Biomedical engineering online
INTRODUCTION: Brucella spondylitis (BS) and tuberculous spondylitis (TS) are prevalent spinal infections with distinct treatment protocols. Rapid and accurate differentiation between these two conditions is crucial for effective clinical management; ...

Development of an explainable machine learning model for predicting device-related pressure injuries in clinical settings.

BMC medical informatics and decision making
BACKGROUND: Device-related pressure injury (DRPI) is a prevalent and severe problem for patients using medical devices. Timely identification of patients at high risk of DRPI is crucial for healthcare providers to make informed decisions and prevent ...

The association of life's essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007-2018.

BMC pulmonary medicine
OBJECTIVE: Chronic respiratory diseases (CRDs) and cardiovascular diseases (CVD) share common risk factors and frequently co-occur, leading to poorer outcomes. Life's Essential 8 (LE8), a novel metric for cardiovascular health, may provide insights i...

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BMC medical imaging
BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomography (NCCT) serves as the primary imaging modality for diagnosing acute ischemic stroke. However, due to the small density difference between the infa...

Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.

Scientific reports
Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing significant challenges in providing appropriate care. As the number of dementia cases continues to rise, delivering optimal care becomes more complex. ...

Machine learning models for predicting multimorbidity trajectories in middle-aged and elderly adults.

Scientific reports
Multimorbidity has emerged as a significant public health issue in the context of global population aging. Predicting and managing the progression of multimorbidity in the elderly population is crucial. This study aims to develop predictive models fo...

MMDental - A multimodal dataset of tooth CBCT images with expert medical records.

Scientific data
In the rapidly evolving field of dental intelligent healthcare, where Artificial Intelligence (AI) plays a pivotal role, the demand for multimodal datasets is critical. Existing public datasets are primarily composed of single-modal data, predominant...