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Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
PURPOSE: To establish a predictive model for the sonication energy required for focused ultrasound surgery (FUS) of breast fibroadenomas.

A novel machine-learning algorithm to screen for trisomy 21 in first-trimester singleton pregnancies.

Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
BACKGROUND: Antenatal screening for Trisomy 21 (T21) in the UK is performed primarily in the first trimester. Nuchal Translucency (NT), gestational age, Free β-HCG and PAPP-A are used in combination, creating the 'combined' test. Multivariate Gaussia...

Large language models' knowledge of children's memory and suggestibility: Evaluating model predictions of prior experimental results.

Acta psychologica
BACKGROUND: Accurately predicting children's memory and suggestibility in forensic contexts, such as child sexual abuse (CSA) investigations, remains challenging for human professionals. Large Language Model (LLM), as an advanced natural language pro...

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...

UBE2D1 as a key biomarker in systemic juvenile idiopathic arthritis: a new perspective on diagnosis and disease activity assessment.

Arthritis research & therapy
BACKGROUND: Early diagnosis is crucial for reducing disability and improving long-term prognosis in patients with systemic Juvenile Idiopathic Arthritis (sJIA), but it remains a significant challenge. This study aims to identify non-invasive biomarke...

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...