“EfficientNet-B0 outperformed DenseNet121, achieving an accuracy of 84.6%, F1-score of 0.8899, and MCC of 0.6849.”

“One doctor claims it's 98 percent accurate.”

“Yet none of the releases are cleared as medical devices, approved for clinical use, or available for direct patient diagnosis—despite marketing language emphasising healthcare transformation.”

“These findings strongly support a human-in-the-loop (HITL) workflow in which the on-premise LLM serves as a collaborative tool, not a full replacement.”

“Finding a tool that diagnoses your hidden talents in 30 seconds using AI!”

“three in five Brits now use AI to self-diagnose health conditions”

“AI misses nearly one-third of breast cancers, study finds”

“The feature, which is expected to roll out in the coming weeks, will offer a dedicated space for conversations with ChatGPT about health.”

“Transfer learning with fine-tuning substantially outperforms CNNs trained from scratch for pediatric pneumonia detection, showing near-perfect accuracy.”

“A tool for spotting pancreatic cancer in routine CT scans has had promising results, one example of how China is racing to apply A.I. to medicine's tough problems.”

““Chat was there for me, calm and rational, helping me strategize, always planning.” and “I see Chat like a last-year medical student: doesn't have a license, isn't…”,”

“CPJ significantly improves performance: using GPT-5-mini captions, GPT-5-Nano achieves +22.7 pp in disease classification and +19.5 points in QA score over no-caption baselines.”

“BatteryAgent effectively corrects misclassifications on hard boundary samples, achieving an AUROC of 0.986, which significantly outperforms current state-of-the-art methods.”

“The paper proposes a multi-modal cross-domain mixed fusion model with dual disentanglement for fault diagnosis.”

“The proposed system consistently outperformed flat multi-class classifiers and pre-trained self-supervised models.”

“CPR achieves an F1 score of 0.632 under SAP attacks, surpassing Median Smoothing (0.541 F1) by 9.1%.”

“The optimal pipeline (ANOVA feature selection with a support vector machine) achieved a mean validation accuracy of 0.79.”

“Novice endoscopists exposed to EndoRare-generated cases achieved a 0.400 increase in recall and a 0.267 increase in precision.”

“PGMP framework outperforms state-of-the-art methods on unseen anatomy, setting new benchmarks in efficiency and diagnostic reliability.”

“The proposed model achieves 95.5% and 98.5% accuracy for 4-class and 2-class imbalanced classification problems, respectively.”

“BATISNet outperforms existing methods in tooth integrity segmentation, providing more reliable and detailed data support for practical clinical applications.”

“MedKGI improves dialogue efficiency by 30% on average while maintaining state-of-the-art accuracy.”

“The device enables self-powered, polarization-sensitive and frequency-selective THz detection across a broad response spectrum from 0.25 to 4.24 THz, with a responsivity of 6 V/W, a response time of 62 ms, and mechanical robustness maintained over 2000 bending cycles.”

“The Hilbert-VLM model achieves a Dice score of 82.35 percent on the BraTS2021 segmentation benchmark, with a diagnostic classification accuracy (ACC) of 78.85 percent.”

“McCoy orchestrates an LLM to translate medical literature into ASP code, combines it with patient data, and processes it using an ASP solver to arrive at the final diagnosis.”

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“PathFound integrates pathological visual foundation models, vision-language models, and reasoning models trained with reinforcement learning to perform proactive information acquisition and diagnosis refinement.”

“MedGemma-4b-it model, fine-tuned using Low-Rank Adaptation (LoRA), demonstrated superior diagnostic capability by achieving a mean test accuracy of 80.37% compared to 69.58% for the untuned GPT-4.”

“The paper introduces the first specialized dataset for weak signal feature learning, containing 13,158 spectral samples, and proposes a dual-view representation and a PDVFN model.”

“The system delivers interpretable, real-time predictions via Explainable AI (XAI) visualizations, supporting transparent clinical decision-making.”

“The article is likely a research paper, so direct quotes are not available in this summary. The core concept revolves around using deep learning and UAVs for agricultural applications.”

“MetaCD outperforms other baselines in both accuracy and generalization.”

“While models achieve up to 69% accuracy on basic literacy tasks, performance declines sharply to 25% on discovery-level challenges.”

“INTERACT-CMIL achieves consistent improvements over CNN and foundation-model (FM) baselines, with relative macro F1 gains up to 55.1% (WHO4) and 25.0% (vertical spread).”

“The study highlights the potential of deep learning methods in enhancing the diagnosis of respiratory diseases such as COVID-19, lung cancer, and pneumonia from chest x-rays.”

“The research focuses on root cause analysis of code-related incidents in cloud applications.”

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“"Through 3-5 efficient interaction rounds, Erkang Diagnosis can accurately understand user symptoms, conduct preliminary analysis, and provide valuable diagnostic suggestions and health guidance."”

“Results showed that all the models achieved high segmentation accuracy, emphasizing the necessitate of grain detection as a critical step in mycetoma diagnosis.”

“CardioMM achieves state-of-the-art performance and exhibits strong zero-shot generalization, even at 24x acceleration, preserving key cardiac phenotypes and diagnostic image quality.”

““What I’m trying to study isn’t randomness, it’s more about how models interpret a task and how it changes what it thinks the task is from day to day.””

“UltraLBM-UNet is a novel model for skin lesion segmentation.”

“The weighted MCC values are higher for classifiers that perform better on highly weighted observations, and hence is able to distinguish them from classifiers that have a similar overall performance and ones that perform better on the lowly weighted observations.”

“FETAL-GAUGE is a benchmark for assessing vision-language models in Fetal Ultrasound.”

“The research focuses on a 'Tool Bottleneck Framework' for medical image understanding.”

“The paper focuses on improving both accuracy and explainability in the context of medical image analysis.”

“The research utilizes angiography-based data-driven methods for assessment.”

“This new solution reduced their feature engineering time from weeks to hours, while maintaining the high clinical standards required by healthcare providers.”

“The article presents a DeepSeek-powered AI system.”

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