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PESI-MS combined with AI to build a prediction model for lymph node metastasis of papillary thyroid cancer.

Pathology, research and practice
OBJECTIVE: Construct a prediction model for lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) using Probe Electrospray Ionization Mass Spectrometry (PESI - MS) combined with artificial intelligence (AI), to assist in the preoperative p...

Visceral Fat Quantified by a Fully Automated Deep-Learning Algorithm and Risk of Incident and Recurrent Diverticulitis.

Diseases of the colon and rectum
BACKGROUND: Obesity is a risk factor for diverticulitis. However, it remains unclear whether visceral fat area, a more precise measurement of abdominal fat, is associated with the risk of diverticulitis.

FedSynthCT-Brain: A federated learning framework for multi-institutional brain MRI-to-CT synthesis.

Computers in biology and medicine
The generation of Synthetic Computed Tomography (sCT) images has become a pivotal methodology in modern clinical practice, particularly in the context of Radiotherapy (RT) treatment planning. The use of sCT enables the calculation of doses, pushing t...

Prediction model of ipsilateral level II lymph node metastasis in papillary thyroid carcinoma.

Auris, nasus, larynx
OBJECTIVES: This study aimed to develop a predictive model for ipsilateral level II lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) using machine learning techniques. The necessity of level II dissection in lateral neck...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Behaviour research and therapy
Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issues in those with depression. However, fewer studies have focused on the predictors of SA in adolescen...

Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces.

Computers in biology and medicine
Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of th...

Improving the mapping of leisure-time physical activity inequities: the use of artificial intelligence to advance estimates of small-areas in Brazil.

Public health
OBJECTIVE: We estimated the prevalence of leisure-time physical activity (LTPA) in small areas of the city of Belo Horizonte and analyzed inequities across areas and between two time periods, 2009-2013 and 2014-2018.

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Psychiatry research
Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized clinical trials in major depressive disorder (MDD). The objective of this study is to develop artificial neural network (ANN) models to predict the indi...