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Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.

Approximately half of generalised anxiety disorder (GAD) patients do not recover from first-line treatments, and no validated prediction models exist to inform individuals or clinicians of potential treatment benefits. This study aimed to develop and validate an accurate and explainable prediction model of post-treatment GAD symptom severity. Data from adults receiving treatment for GAD in eight I...

Real-World Outcomes of Patients with Advanced Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer in Canada Using Data Extracted by Large Language Model-Based Artificial Intelligence.

Real-world evidence for patients with advanced -mutated non-small cell lung cancer (NSCLC) in Canada is limited. This study's objective was to use previously validated DARWEN artificial intelligence (AI) to extract data from electronic heath records of patients with non-squamous NSCLC at University Health Network (UHN) to describe mutation prevalence, treatment patterns, and outcomes. Of 2154 pat...

Research on helmet wearing detection method based on deep learning.

The vigorous development of the construction industry has also brought unprecedented safety risks. The wearing of safety helmets at the construction s...

Amount Estimation Method for Food Intake Based on Color and Depth Images through Deep Learning.

In this paper, we propose an amount estimation method for food intake based on both color and depth images. Two pairs of color and depth images are ca...

Comparative analysis of radiation exposure in robot-assisted total knee arthroplasty using popular robotic systems.

Robotic-assisted TKA (RATKA) is a rapidly emerging technique that has been shown to improve precision and accuracy in implant alignment in TKA. Roboti...

Effect of different targets of goal-directed fluid therapy on intraoperative hypotension and fluid infusion in robot-assisted laparoscopic gynecological surgery: a randomized non-inferiority trial.

Carotid corrected flow time (FTc) and tidal volume challenge pulse pressure variation (VtPPV) are useful clinical parameters for assessing volume stat...

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmac...

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework.

PURPOSE: Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor meas...

Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing.

The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units o...

Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets.

OBJECTIVE: The primary objective of this review is to investigate the effectiveness of machine learning and deep learning methodologies in the context...

Exploring the Use of Socially Assistive Robots Among Socially Isolated Korean American Older Adults.

This pilot study explored whether a socially assistive robot (SAR) would have positive effects on Korean American immigrant older adults' health behav...

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images.

A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both non-contrast and ...

An artificial intelligence algorithm for co-clustering to help in pharmacovigilance before and during the COVID-19 pandemic.

AIMS: Monitoring drug safety in real-world settings is the primary aim of pharmacovigilance. Frequent adverse drug reactions (ADRs) are usually identi...

Extracting adverse drug events from clinical Notes: A systematic review of approaches used.

BACKGROUND: An adverse drug event (ADE) is any unfavorable effect that occurs due to the use of a drug. Extracting ADEs from unstructured clinical not...

Detection method of organic light-emitting diodes based on small sample deep learning.

In order to solve the surface detection problems of low accuracy, low precision and inability to automate in the production process of late-model disp...

Two is better than one: longitudinal detection and volumetric evaluation of brain metastases after Stereotactic Radiosurgery with a deep learning pipeline.

PURPOSE: Close MRI surveillance of patients with brain metastases following Stereotactic Radiosurgery (SRS) treatment is essential for assessing treat...

Incidence and risk factors of inguinal hernia after robot-assisted radical prostatectomy: a retrospective multicenter cohort study in Japan (the MSUG94 group).

To investigate the incidence and risk factors of inguinal hernia (IH) after robot-assisted radical prostatectomy (RARP) using a multicentric database....

Prediction of adverse events risk in patients with comorbid post-traumatic stress disorder and alcohol use disorder using electronic medical records by deep learning models.

BACKGROUND: Identifying co-occurring mental disorders and elevated risk is vital for optimization of healthcare processes. In this study, we will use ...

Phytochemical and biological studies of aerial parts ethanol extract supported by molecular docking study.

has traditionally been used as a poultice to alleviate local inflammation and painful diseases. This study aimed to evaluate the anti-inflammatory, w...

BKPyV DNAemia in Kidney Transplant Recipients Undergoing Regular Screening: A Single-Centre Cohort Study.

Infection with BK polyomavirus (BKPyV) is a common opportunistic infection after kidney transplantation (KT) and may affect graft function. We aimed t...