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PolicyEvidence-backed problem

House speaker calls early recess before midterms amid AI regulation frenzy

The Republican speaker of the House, Mike Johnson, announced on Wednesday that he would again cancel votes scheduled for Thursday, sending lawmakers home one day early ahead of the midterm election recess. The latest change to the legislative schedule means House members will avoid voting on Republican Thomas Massie’s resolution to impeach the defense secretary, Pete Hegseth, and comes amid a frenzied attempt to propose legislation on artificial intelligence. It’s the latest round of cancellations at the hands o…

The Guardian

Evidence-backed problem

A fake image of a Georgia mayor kissing a person went viral. Can US voters trust everything they see?

Evidence-backed gain

Integrated Multi-Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC

Evidence-backed gain

Machine learning-based discrimination of metabolic dysfunction-associated steatotic liver disease: implications of tryptophan metabolites as potential biomarkers

Both readings

Evaluation of the detection accuracy of a fully automated AI-based lesion segmentation tool in whole-body FDG PET/CT for lymphoma

Background This study evaluated an AI-based lesion segmentation tool using a hybrid 2D-3D deep learning model based on the nnUNet architecture with a ResNet18 backbone, incorporating post-processing to reduce false positives and segmentation-related quantitative errors. Methods Whole-body FDG PET/CT scans from 72 lymphoma patients (mean age 39.2 ± 18.6 years; 33 females, 39 males; 43.1% Hodgkin lymphoma, 56.9% non-Hodgkin lymphoma) acquired on a uMI550 digital PET/CT system were retrospectively analysed. Automat…

Evidence-backed gain

Machine learning-based nomogram for acute kidney injury after liver transplantation

Acute kidney injury (AKI) after liver transplantation (LT) is a frequent complication associated with adverse outcomes, yet practical early postoperative prediction tools remain limited. This retrospective study developed and internally validated an interpretable model for AKI after LT using perioperative variables available by the time of the first urgent postoperative blood test, generally obtained within 1 h after surgery. Adult LT recipients treated from June 2023 to January 2026 were screened. AKI was defin…

Both readings

Cardiovascular Classification in Middle-Aged and Elderly CKD Patients: A Machine Learning Approach in China and the United States

Background Cardiovascular disease (CVD) drives mortality in chronic kidney disease (CKD) patients. Conventional risk tools underperform in CKD, and few machine learning (ML) models undergo cross-national validation. We developed interpretable ML models for classifying CVD amongst Chinese and US middle-aged and elderly CKD patients. Methods We conducted retrospective cross-sectional analyses using two nationally representative cohorts: NHANES (2011-2016, US) and CHARLS (Wave 1 and 3, China). A total of 1057 CKD p…

Both readings

Deep Learning and Machine Learning Algorithms for Cervical Cancer Segmentation on MRI: A Systematic Review

Introduction Cervical cancer management relies heavily on magnetic resonance imaging (MRI) for staging and treatment planning; however, manual segmentation is time-consuming and prone to variability. This systematic review aimed to evaluate the performance and clinical potential of machine learning (ML) and deep learning (DL) algorithms for automated cervical cancer segmentation on MRI. Methods A systematic review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (PROSPERO…

Health

Exploring the Potential of Parent Report for Autism/Developmental Screening at the 18-Month Visit

Purpose To develop optimal algorithms of parent-administered items to improve the detection of autism and other developmental disorders at the 18-month visit. Methods Parents of 11,878 children aged 16-20 months completed the M-CHAT-R/F ™ , Q-CHAT-10-O, and ASQ-3 R at scheduled 18-month pediatric visits via an online system. Ninety-six children with positive screens and 314 matched controls completed additional items, including the POSI; items from the FYI and POEM data banks, and the MacArthur-Bates Communicati…

Policy

Comparative hydro-climatic forecasting of reservoir storage and cross-scale bathymetric evaluation in Mingde and Shihmen reservoirs

Accurate reservoir storage forecasting is critical for water security and risk management, yet most data-driven approaches emphasize short-term predictive skill without accounting for long-term changes in storage capacity caused by sedimentation. This study addresses this gap by examining whether monthly, hydro-climatic machine learning forecasts of effective water storage capacity can be meaningfully evaluated against observed, multi-year capacity changes derived from bathymetric surveys. Forecasting performanc…

Science

Artificial Intelligence in Organic Synthesis

Artificial intelligence (AI) is rapidly reshaping organic synthesis; nevertheless, currently most laboratory practice still remains driven by human intuition, trial-and-error optimization, and manual interpretation of analytical data. Here, we synthesize recent advances that move AI from isolated demonstrations to a practical toolkit spanning the full experimental cycle: molecular design and prioritization, computer-assisted synthesis planning and route selection, catalyst and condition optimization, and AI-enab…

Health

Normalized risk-based evaluation of machine learning-based classification models: A multiclass approach with applications in medical devices

ObjectiveMachine learning is increasingly integrated into safety-critical domains such as medical applications. In this context, regulatory frameworks require the assessment and minimization of risks associated with incorrect model predictions. However, classical evaluation methods often focus on quantifying error frequencies, which do not reflect the heterogeneous impact of different types of errors. To address this deficiency, we elaborate an approach for assessing machine learning-based multiclass classificat…

Media & Arts

MakeBestMusic Upgrades AI Music Platform With Section-Specific Chorus Regeneration and Stem Isolation Tools

New workflow update addresses repetitive musical hooks in AI-generated tracks, giving creators greater control over chorus variation and arrangement

Crime

Trial of live facial recognition in London stations leads to a false positive and no arrests

A six-month trial of live facial recognition (LFR) technology in London’s railway stations that cost more than £320,000 and almost 100 hours of police officers’ time led to one false match against a watchlist of suspects and no arrests. More than half a million faces were scanned between February and July this year in some of the capital’s busiest transport hubs during the British Transport Police (BTP) trial of the surveillance technology, which aimed to help catch offenders and people breaching court orders. A…

Policy

Trump announces vague ‘morally binding’ AI deal among tech CEOs for ‘tremendous self-policing’

Donald Trump announced on Tuesday that the heads of the largest US tech and AI companies had signed on to a “morally binding” agreement to put controls on artificial intelligence. He announced the deal, called the Joint Commitment On Frontier Responsibilities, following a White House luncheon with top tech executives. “It’s almost like a constitution in a way, and the biggest people in the world signed that, and I signed it as president, and it really ⁠is a form of protection,” Trump said. Trump also signed an e…