Preventive Care

Predicting suicidal ideation from depression screening data: A network-augmented machine learning approach.

BACKGROUND: Suicidal ideation is often assessed using a single self-report item in routine screening. We developed a model that combines machine learning with symptom-network analytics to infer an auxiliary signal relevant to suicidal ideation from routine depressive-symptom data. METHODS: Adults from the National Health and Nutrition Examination Survey (N = 44,922) were used to predict ideation (...

Negligible impact of perifissural nodules in an AI-first reader workflow from UK lung screening trial.

OBJECTIVE: To evaluate the effect of perifissural nodules (PFNs) on radiologist workload within an AI-first reader workflow for lung cancer screening, given that AI cannot morphologically classify benign PFNs measuring ≥ 100 mm3. MATERIALS AND METHODS: One thousand two hundred fifty baseline low-dose CT scans from the UK Lung Screening (UKLS) Trial were analyzed. A commercially available AI softwa...

Artificial intelligence in cancer screening: a narrative review of current evidence and future directions.

INTRODUCTION: Cancer remains one of the leading causes of death worldwide, with outcomes improving significantly when the disease is detected at an ea...

Development and validation of a risk prediction model for diabetic peripheral neuropathic pain in type 2 diabetes: A machine learning and statistical approach.

OBJECTIVE: To identify independent risk factors for diabetic peripheral neuropathic pain (DPNP), construct a nomogram prediction model, and quantify t...

Impact of Computer-Aided Detection on Endoscopist's Gaze-Shift Distance During Colonoscopy: a Randomized Controlled Trial (With Video).

BACKGROUND AND AIM: Computer-aided detection (CADe) facilitates colorectal lesion detection, but it remains unclear whether CADe affects endoscopist's...

Validation of an AI-assisted screening tool for lameness detection in dairy cattle: A field-based study for preventive herd health management.

Lameness is a major welfare and economic challenge in the dairy industry, requiring effective surveillance tools for herd-level management. While visu...

Evaluating the accuracy of screening titles and abstracts for progressing to full-text screening by one vs two independent reviewers: part 1 of a meta-research study of rapid review methodological trade-offs.

OBJECTIVES: To determine the accuracy for progressing records to full-text screening using one vs two reviewers to screen title and abstracts in 3 rev...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Artificial intelligence in medicine: a scoping review of the risk of deskilling and loss of expertise among physicians.

BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and ...

AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.

Artificial intelligence (AI) systems have been demonstrated to improve the accuracy of screening mammograms. Here this prospective, paired, noninferio...

Predicting toxicity and bioactivity of the chemical exposome: a case study for the blood exposome database.

Humans are exposed to thousands of chemicals throughout their life. Many of these chemicals are detected in blood and have been catalogued in the Bloo...

Comment on "The optimal labelling method for artificial intelligence-assisted polyp detection in colonoscopy".

Comment on "The optimal labelling method for artificial intelligence-assisted polyp detection in colonoscopy".

Genomic evolution of SARS-CoV-2 delta variants pre- and post-omicron emergence using alignment-free machine learning models.

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

PURPOSE: Digital cough screening for COVID-19 detection shows promise, but population differences in cough acoustics and screening accuracy require in...

Thymic health consequences in adults.

The thymus is essential for establishing T cell diversity early in life, but undergoes profound involution with age and has therefore traditionally be...

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results.

LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or rarely encountered compound is tentatively identifie...

A Machine Learning-Based Clinical Tool for Predicting Inadequate Bowel Preparation: Development and Validation.

OBJECTIVES: Colonoscopy is an essential tool for diagnosing and treating colorectal diseases, with bowel preparation serving as a key determinant of i...

Early cognitive screening for individuals on the dementia continuum: A novel approach amid current trends.

Mild cognitive impairment (MCI) is a critical transitional stage between normal aging and dementia that remains challenging to detect. Many traditiona...

The Burden, Outcomes, and Management of Patients with Aldosterone Dysregulation: A Targeted Literature Review.

INTRODUCTION: Aldosterone dysregulation (excess aldosterone production at the source within the adrenal glands) in the absence of primary aldosteronis...