+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
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1045 published stories · page 5 of 70

Evidence-backed gain

Machine learning insights into band gap properties in halide-based perovskites

Halide perovskites show great promise for applications in optoelectronic devices. The lead-free perovskites are attracting increasing interest due to their low toxicity and motivate the exploration of alternative compositions and structures, including A 2 BX 6 , A 2 BB'X 6 , A 3 B 2 X 9 , and A 4 BX 6 . Accurate predictions of a wide range of band gap energies are important for designing new materials. It is also important to generate a direct relationship between the structural and elemental descriptors and the…

Physical Chemistry Chemical Physics · Science

Machine learning insights into band gap properties in halide-based perovskites
A Multiparametric Approach Integrating Multimodal Ultrasound and Serum TPO-Ab for Differentiating Thyroid Carcinoma in Hashimoto's Thyroiditis: A Comparative Diagnostic Study with Internal Validation
Evidence-backed gain

A Multiparametric Approach Integrating Multimodal Ultrasound and Serum TPO-Ab for Differentiating Thyroid Carcinoma in Hashimoto's Thyroiditis: A Comparative Diagnostic Study with Internal Validation

Objectives To evaluate whether a multiparametric approach combining grayscale ultrasound (2D-US), contrast-enhanced ultrasound (CEUS), and serum anti-thyroid peroxidase antibody (TPO-Ab) improves the differentiation of benign from malignant thyroid nodules (TNs) in patients with Hashimoto's thyroiditis (HT) and to assess the stability of the combined diagnostic model through internal validation. Methods This retrospective study enrolled 600 HT patients with 650 pathologically confirmed TNs. All patients underwen…

Health
Developing validity arguments for artificial intelligence-based assessment: Balancing affordances and threats
Both readings

Developing validity arguments for artificial intelligence-based assessment: Balancing affordances and threats

Background Artificial intelligence (AI) is increasingly used to generate, score and interpret educational assessment, yet these applications are being adopted in a largely unregulated environment. This creates a paradox: Whereas AI systems used in clinical care are subject to formal scrutiny for safety, performance and monitoring, AI systems used to inform consequential decisions about learner progression and future clinical practice are not. Existing validity frameworks remain useful but may not fully account f…

Education
An integrative clinical-molecular model as an auxiliary predictive tool for glioma malignancy grade
Both readings

An integrative clinical-molecular model as an auxiliary predictive tool for glioma malignancy grade

Objective An integrative auxiliary predictive model incorporating clinical parameters, serum biomarkers, and molecular pathological markers was developed to assess glioma malignancy grade. Methods This single-center retrospective observational study consecutively enrolled 400 glioma patients. A total of 26 variables, including demographic characteristics, clinical parameters, laboratory indicators, and serum biomarkers, were analyzed. Predictors were selected using univariate analysis, followed by Least Absolute…

Health
Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review
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Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review

Background Neonatal heart rate (HR) is an important parameter in the evaluation of newborn health and viability in the immediate postnatal period. Aim To evaluate the accuracy, reliability, and clinical applicability of emerging non-contact and artificial intelligence (AI)-assisted HR monitoring technologies in neonates compared to conventional electrocardiography (ECG)-based systems. Methods A comprehensive literature search was conducted across PubMed, EMBASE, Google Scholar, and Cochrane databases from Januar…

Health
Artificial intelligence for early sepsis detection and dynamic prognostication in onco-critical care
Evidence-backed gain

Artificial intelligence for early sepsis detection and dynamic prognostication in onco-critical care

Critically ill cancer patients have a unique physiological profile marked by severe immunosuppression, frailty, and multimorbidity, making traditional tools like Acute Physiology and Chronic Health Evaluation II or Sequential Organ Failure Assessment often inadequate for accurate risk assessment. This review explores artificial intelligence's potential to transform onco-critical care from reactive to predictive management. We will synthesize literature on two key applications: Early sepsis detection in criticall…

Health
Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation
Evidence-backed gain

Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation

Mechanical ventilation has evolved into a complex intervention that influences lung injuries, respiratory muscle function, and hemodynamic stability. Although lung-protective strategies improve outcomes in acute respiratory distress syndrome, bedside management remains limited by incomplete monitoring of key physiologic variables, including lung stress, inspiratory effort and regional ventilation. This constrains decision such as positive end-expiratory pressure titration and ventilatory assist targeting. Emergi…

Health

OpenAI claims to have solved maths problem that stumped humans for decades

OpenAI claims to have solved a major mathematics problem that has stumped humans for nearly a century after spending millions of dollars on the artificial intelligence-led endeavour. The company behind ChatGPT said it had cracked the Navier-Stokes problem, one of seven Millennium Prize Problems published by the Clay Mathematics Institute to highlight some of the biggest unsolved puzzles in the field. However, the announcement swiftly became mired in controversy after mathematician Tristan Buckmaster, a professor…

Science
OpenAI claims to have solved maths problem that stumped humans for decades

AI will help find cure for cancer ‘within our lifetimes’, says Arm Holdings chief

The boss of one of the UK’s biggest chip companies has claimed AI will be able to find a cure for cancer “in our lifetime”. Rene Haas, chief executive of the chip designer Arm Holdings, said that, while modelling how a DNA marker is affected by cancer was currently “too complex” a problem for either humans or technology, computers were “going to solve it” in the future. Haas told the BBC: “AI is going to … find a cure for cancer that today you and I, other humans [could] not in our lifetimes. I believe in our li…

Health
AI will help find cure for cancer ‘within our lifetimes’, says Arm Holdings chief

Select large language models outperform hip preservation experts on consensus-based hip preservation questionnaire

Artificial intelligence (AI) is increasingly utilized in medical education and clinical contexts, yet few studies compare the performance of large language models (LLMs) to subspecialized experts in providing guideline-based medical information on hip preservation. The purpose of this study was to evaluate the performance of three LLMs compared to a panel of international hip preservation experts in answering guideline-based questions related to femoroacetabular impingement syndrome, hip dysplasia and microinsta…

Health
Select large language models outperform hip preservation experts on consensus-based hip preservation questionnaire

From Correlation to Clinical Translation: The Biological-Grounding×Translational-Readiness Framework for Artificial Intelligence in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer death worldwide, and clinicians now face a rapidly expanding array of artificial intelligence (AI) tools promising earlier detection, better treatment selection, and more precise radiotherapy, yet few have altered what happens at the bedside. The problem is not poor benchmark performance; it is that strong benchmark performance has repeatedly failed to translate into demonstrable patient benefit, because most published NSCLC models are retros…

Health
From Correlation to Clinical Translation: The Biological-Grounding×Translational-Readiness Framework for Artificial Intelligence in Non-Small-Cell Lung Cancer

NDIB-Sim: A Multimodal Bidirectional PINN Model for Simulating Brain Dynamics

Constructing dynamic virtual brain models is essential for understanding brain functions and pathological mechanisms, crucial in computational neuroscience. Current modeling methods can be grouped into two paradigms: deep learning models for accurate simulation, and neural dynamics models emphasizing physiological interpretability. However, these methods entail a fundamental tradeoff between accuracy and interpretability. To address this challenge, we introduce the neurodynamics-informed brain simulator (NDIB-Si…

Health
NDIB-Sim: A Multimodal Bidirectional PINN Model for Simulating Brain Dynamics

SnSe/SnO2 Heterojunction-Based Single-Sensor Virtual Electronic Nose with Low Reaction Barrier for Trace Identification of Volatile Sulfur Compounds toward Illicit Methamphetamine Trafficking Traceability

Illicit methamphetamine (MA, ice) trafficking poses a severe global threat to public security, while non-contact on-site detection of MA remains a grand challenge due to its ultra-low saturated vapor pressure at room temperature (25 °C). Volatile sulfur compounds (VSCs), including hydrogen sulfide (H2S), methanethiol (CH3SH), and dimethyl sulfide (C2H6S, DMS), are stable characteristic markers released throughout the entire MA production, purification, storage, and transportation chain. Herein, we develop a sing…

Crime
SnSe/SnO2 Heterojunction-Based Single-Sensor Virtual Electronic Nose with Low Reaction Barrier for Trace Identification of Volatile Sulfur Compounds toward Illicit Methamphetamine Trafficking Traceability