Addictions

Robotic thoracic surgery: what is different in anesthesia?

PURPOSE OF REVIEW: Robotic-assisted thoracic surgery (RATS) has emerged as a transformative approach in thoracic surgery, enabling enhanced precision and minimally invasive treatment for lung, esophageal, and mediastinal resections. These advances introduce unique anesthetic challenges requiring tailored strategies to ensure patient safety and surgical success. RECENT FINDINGS: Key challenges incl...

Artificial intelligence-based models for clinical prognosis at the end of life in the ICU.

INTRODUCTION: Artificial intelligence (AI) has emerged as a promising tool to enhance clinical prediction in critically ill patients near the end of life in the intensive care unit (ICU), overcoming the limitations of traditional prognostic scales. AIM: To identify and describe artificial intelligence models implemented to support prognostic decisions at the end of life in the intensive care unit ...

A prospective study evaluating an artificial intelligence-based system for withdrawal time measurement.

Withdrawal time has emerged as a critical quality measure in colonoscopy for colorectal cancer screening. Owing to the high variability in calculating...

A novel machine learning-based method to quantify the effect of transcranial direct current stimulation on opioid users.

BACKGROUND: Opioid addiction is a major public health concern, associated with numerous health and social problems. Conventional diagnostic methods fo...

Impact of artificial intelligence-assisted colonoscopy on gastroenterology fellow performance: a pragmatic randomized controlled trial.

BACKGROUND AND AIMS: The substantial miss rate during screening and surveillance colonoscopy, particularly for the right side, underscores the need to...

From Screening to Safety: Addressing Donor Deferral Practices for a Safer Blood Supply.

For ensuring blood safety, potential blood donors undergo comprehensive eligibility screening, comprising a review of their medical history and a phys...

Causal Transformer for Learning Embeddings from Structured Medical History Records and Multi-Source Data Integration for Complex Disease Risk Prediction.

Traditional disease risk prediction models predominantly rely on statistical algorithms and often focus on genetic factors or a limited set of lifesty...

Ex vivo human brain volumetry: Validation of MRI measurements.

PURPOSE: The volume of in vivo human brains is determined with various MRI measurement tools that have not been assessed against a gold standard. The ...

The prognostic significance of metabolic score for insulin resistance in evaluating all-cause and cardiovascular mortality risk among individuals across stages 1-4 of cardiovascular-kidney-metabolic syndrome: a nationwide prospective cohort study.

BACKGROUND AND AIM: Cardiovascular-kidney-metabolic syndrome (CKM) embodies the intricate interaction among metabolic, kidney, and cardiovascular dysf...

Multi-component collaborative design yields robust hydrogel sensors with superior environmental adaptability for machine learning-assisted gesture recognition.

Developing high-performance wearable flexible sensors that can adapt well to complex environments has become a hotspot. Herein, a polyvinyl alcohol ba...

Impulsivity and neuroticism share distinct functional connectivity signatures with alcohol-use risk in youth.

Increases in impulsivity and negative affect (e.g., neuroticism) are common during adolescence and are both associated with risk for alcohol-use initi...

Acceptability and feasibility of a new-generation alcohol biosensor: A mixed methods evaluation in a large community sample.

Wearable alcohol biosensors offer an innovative solution for real-time alcohol monitoring, yet concerns about comfort, privacy, and social acceptabili...

Prediction of Response to Spinal Cord Stimulation Using Machine Learning Based on Radiomics and Patient-Reported Outcomes.

BACKGROUND AND OBJECTIVES: Chronic pain affects more patients than cancer, diabetes, and heart disease combined, resulting in high morbidity and signi...

Warning: AI chatbots will soon dominate psychotherapy.

Psychotherapy chatbots have attained remarkable fluency, skill and ubiquity - having become the single most frequent reason people use artificial inte...

Efficacy of artificial intelligence for adenoma detection in water exchange colonoscopy: a two-center randomized controlled trial.

Water exchange and artificial intelligence-based computer-aided detection (CADe) separately improve the adenoma detection rate (ADR) and number of ade...

Algal/bacterial membrane bioreactor for bioremediation of hazardous landfill leachate containing 1,4-dioxane: An artificial neural network modeling.

This study developed an artificial neural network (ANN) model to predict the 1,4-dioxane removal efficiency from hazardous landfill leachate treated b...

FEAOF: A transferable framework applied to prediction of hERG-related cardiotoxicity.

Inhibition of the hERG (human ether-a-go-go-related gene) channel by drug molecules can lead to severe cardiac toxicity, resulting in the withdrawal o...

A machine learning-driven transcriptomic study reveals the key role of Romo1 in reversing central sensitization through stellate ganglion block in migraine: An interventional study based on a recurrent migraine rat model.

OBJECTIVES/BACKGROUND: This study utilized a nitroglycerin (NTG)-induced chronic migraine rat model to explore the therapeutic effects and underlying ...

A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.

INTRODUCTION: Drug-induced Torsades de Pointes (TdP) has led to withdrawal of several drugs from the market. Individuals with inherited cardiac channe...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms rem...