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Large Language Model-Based Localization of Premature Ventricular Contraction Origins: A Retrospective Diagnostic Accuracy Study
HealthEvidence-backed gain

Large Language Model-Based Localization of Premature Ventricular Contraction Origins: A Retrospective Diagnostic Accuracy Study

Background Accurate localization of premature ventricular contraction (PVC) origin from 12-lead electrocardiography (ECG) is important for procedural planning in catheter ablation. Although convolutional neural network (CNN)-based models have shown promising diagnostic performance, they require task-specific training and remain limited in interpretability. We evaluated whether large language model (LLM)-based ECG image interpretation could perform binary left-versus-right PVC origin localization from 12-lead ECG…

Journal of Cardiovascular Electrophysiology
Integrating network toxicology, machine learning, and single-cell sequencing systems to analyze autophagy core genes in lung adenocarcinoma
Evidence-backed gain

Integrating network toxicology, machine learning, and single-cell sequencing systems to analyze autophagy core genes in lung adenocarcinoma

The heterogeneity and complex tumor microenvironment of lung adenocarcinoma lead to poor prognosis. Autophagy, as a key cellular process, interacts with tumor immune infiltration and jointly affects the progression of lung adenocarcinoma, but its core regulatory genes and mechanisms are still unclear.This study integrated three lung adenocarcinoma transcriptome datasets from the GEO database and performed cross-analysis with the human autophagy gene set to screen for differentially expressed autophagy-related ge…

Delhi HC protects Yuvraj Singh's personality rights, says AI-generated deepfakes, unauthorised commercial use tarnish reputation, violate law
Evidence-backed problem

Delhi HC protects Yuvraj Singh's personality rights, says AI-generated deepfakes, unauthorised commercial use tarnish reputation, violate law

The Delhi High Court has protected Yuvraj Singh's personality rights. AI-generated deepfakes and unauthorised exploitation damage his reputation and commercial value. The court issued an interim injunction against creating and publishing such content. This order reinforces celebrity rights in the age of artificial intelligence. Violators of these rights will be dealt with severely.

Smart elections or rigged algorithms: the rise of artificial intelligence in electoral governance in Southeast Asia
Both readings

Smart elections or rigged algorithms: the rise of artificial intelligence in electoral governance in Southeast Asia

Introduction Introducing Artificial Intelligence AI into electoral-management infrastructure has radically transformed the administrative practice in Southeast Asian democracies through streamlining voter registration, consolidating identification, and making the real-time observation of the electoral events possible. Although the benefits of AI are undoubtedly tangible in terms of efficiency, transparency, and accessibility, its appearance in contexts where such regulatory sanitation is antithetical presents sh…

Local Recurrence Prediction After Carbon-ion Radiotherapy for Early-stage Non-small Cell Lung Cancer Using Machine Learning
Evidence-backed gain

Local Recurrence Prediction After Carbon-ion Radiotherapy for Early-stage Non-small Cell Lung Cancer Using Machine Learning

Background/aim Predicting local recurrence remains challenging in carbon-ion radiotherapy (CIRT) for non-small cell lung cancer (NSCLC). In this study, we aimed to develop and validate a machine learning model to predict local recurrence after CIRT for early-stage peripheral NSCLC. Patients and methods We retrospectively analyzed patients treated with CIRT at our institution between 2010 and 2020. An Extreme Gradient Boosting classifier using clinical parameters was developed to predict local recurrence within 2…

Policy

From bones to bytes: anticipating and addressing the governance challenges of human digital remains and posthumous digital human twins

Abstract During the nineteenth century, advances in medical research led to grave robbing and an illicit market in human biological remains (HBR). The historical episode of grave robbing illustrates how science can upend social norms. A similar scenario could soon emerge, but this time it will not be with people's biological remains, but with people's digital remains. Artificial intelligence and extended reality now create digital representations from avatars to human digital twins. In addition to the sophistica…

From bones to bytes: anticipating and addressing the governance challenges of human digital remains and posthumous digital human twins
Health

Screening efficiency over experience: Rapid target detection in low-power field as a modifiable cognitive biomarker for diagnostic accuracy in digital cytology

Background Traditionally, cytology expertise has been equated with professional experience. However, the transition to whole-slide imaging and artificial intelligence (AI) necessitates a shift from exhaustive screening to rapid verification. The goal of this study was to identify cognitive biomarkers associated with diagnostic accuracy and evaluate their modifiability. Methods In phase 1, 100 cytotechnologists with 1-40 years of experience diagnosed 30 digital cytology images using eye-tracking. Gaze metrics acr…

Screening efficiency over experience: Rapid target detection in low-power field as a modifiable cognitive biomarker for diagnostic accuracy in digital cytology
Health

The Sydney Triage to Admission Risk Tool With Artificial Intelligence (START-AI) to Support Decision Making in Emergency Departments: Model Explainability and Feature Importance Analysis

Objective Evaluate the importance of specific variables contributing to a recently reported Artificial Intelligence (AI) prediction model called Sydney Triage to Admission Risk Tool with Artificial Intelligence (START-AI) to predict inpatient admission from the Emergency Department (ED). Methods A model explainability analysis was undertaken using single-centre ED electronic medical record data over 2 years. The START-AI model, which comprises ensemble machine learning and a transformer-based algorithm to enhanc…

The Sydney Triage to Admission Risk Tool With Artificial Intelligence (START-AI) to Support Decision Making in Emergency Departments: Model Explainability and Feature Importance Analysis
Health

[Artificial intelligence in hypertension: where do we stand?]

Artificial intelligence (AI) is entering the study of hypertension, serving both primarily clinical purposes - to assist practicing physicians - and research objectives. Hypertension presents certain specific characteristics that should be carefully considered when using AI. The measured value of blood pressure is an extremely variable parameter that is difficult to standardize and measure with precision. At present, AI is able to provide very simple, clear, and well-documented answers to clinical questions rega…

[Artificial intelligence in hypertension: where do we stand?]
Health

Harnessing Exhaled Breath for Lung Cancer Early Detection-Results From the ExPeL Study

Scalable, non-invasive tools are critically needed to improve early lung cancer detection and optimize primary care referral pathways. We evaluated Inflammacheck, a point-of-care device utilizing exhaled breath condensate (EBC) H 2 O 2 and physiological parameters with machine learning for non-invasive lung cancer detection in a real-world screening population. Exhaled Hydrogen Peroxide for Early Lung Cancer Detection (ExPeL) study participants, from the UK Targeted Lung Health Check (TLHC) programme, included i…

Harnessing Exhaled Breath for Lung Cancer Early Detection-Results From the ExPeL Study
Health

Multiomics Profiling Identifies Blood-Based Diagnostic Markers for Sepsis

Sepsis, characterized by a rapid transition to systemic immune dysregulation and multiorgan failure, poses a formidable clinical challenge. The lack of spatiotemporally stable biomarkers severely impedes early diagnosis and risk stratification. By integrating large-scale transcriptomic profiling with machine learning algorithms, this study identified a robust three-gene diagnostic signature (TLR5, HMGB2, and C19orf59). Single-cell RNA sequencing precisely localized the sepsis-induced specific upregulation of the…

Multiomics Profiling Identifies Blood-Based Diagnostic Markers for Sepsis