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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…

Frontiers in Political Science · Policy

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

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…

Health

Evidence-backed problem

Was Jacqueline Fernandez's Viral 'Wardrobe Malfunction' Clip AI-Generated? Singer Sonu Thukral Files Police Complaint

Singer Sonu Thukral lodges a police complaint after an AI-edited viral clip claiming Jacqueline Fernandez suffered a wardrobe malfunction in the Jugni music video spreads online.

Crime

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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…

Policy

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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…

Health

Evidence-backed gain

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…

Health

Both readings

[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…

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…

Health

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

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…

Health

Bridging the Gap: Translated Medical Education to Support Cystic Fibrosis Centers From Non-English Speaking Countries

Background The European Cystic Fibrosis Society (ECFS) develops education resources to support members; however, these are almost exclusively in English. Many barriers to translation exist, including cost and time. Artificial intelligence (AI) provides an opportunity to support translation and address such barriers. This study aimed to pilot the use of AI-generated translation of ECFS e-learning modules and evaluate the quality. Methods An AI translation program was used to create subtitles of ECFS peer-reviewed…

Education

Large Language Models for Individualized Psychoeducational Tools for Psychosis: A Cross-Sectional Study

Objective This study aimed to evaluate the quality of GPT-4-generated responses to commonly asked psychosis-related psychoeducational questions from patients, caregivers and relatives in a first-episode psychosis programme. Evaluation focused on accuracy, clarity, inclusivity, completeness, clinical utility and overall quality. Design This cross-sectional study employed a qualitative evaluation design. GPT-4, accessed via the ChatGPT interface, generated responses to 20 psychosis-related psychoeducational questi…

Health

Advancing Radiology Education with Artificial Intelligence: Curriculum Planning, Implementation, and Evaluation

Artificial intelligence (AI) is rapidly integrating into clinical radiology, creating a continuous emphasis on the necessity of teaching its principles to radiology trainees. However, the potential of AI to transform radiology education remains underexplored. The authors review how AI can be leveraged to enhance radiology education, from curriculum planning to its implementation and evaluation. Guided by Harden's 10-step framework for curriculum development, they systematically examine current and potential futu…

Health

Machine Learning-Based Prediction of Poor Outcomes in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis

Spontaneous intracerebral hemorrhage (ICH) is associated with high risks of mortality and disability, yet early and accurate outcome prediction remains challenging. This study systematically evaluated the performance of machine learning (ML) models in predicting key adverse outcomes (hematoma expansion [HE], poor functional outcome, mortality) in ICH, aiming to provide consolidated evidence for future research and clinical translation. We systematically searched PubMed, Embase, Web of Science, and Cochrane Libra…

Health

Machine Learning-Based Prediction of Poor Outcomes in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis

Classification of tau status with machine learning models in amyloid-positive cohorts

Although tau positron emission tomography (PET) imaging is effective for staging tau pathology, it is limited clinically by cost and availability. Machine learning models based on magnetic resonance imaging (MRI)- and amyloid PET-derived features may serve as useful screening tools for tau pathology. Multiple machine learning models were developed to classify tau positivity in the Braak III/IV region using structural MRI, amyloid PET, and demographic features. Alzheimer's Disease Neuroimaging Initiative (ADNI) (…

Health

Classification of tau status with machine learning models in amyloid-positive cohorts

Why bad health information can seem so convincing-and five ways to resist it

Recent reports have highlighted AI-generated "doctors" spreading dubious health advice to millions of social media users. Fabricated wellness trends can travel just as quickly. A supposed "pink jelly" weight-loss treatment, for example, reportedly fooled at least one celebrity.

Health