medical imaging

"When a strict subject-level split is enforced, performance drops substantially, yielding test accuracies between 60 and 81 percent."

"The proposed framework achieved an AUC of 0.685 and an F1-score of 0.872 on a private dataset from the UF Integrated Data Repository (IDR), and an AUC of 0.760 and an F1-score of 0.852 on the publicly available KiTS21 dataset."

"Experimental results demonstrate that MNAS-Unet outperforms NAS-Unet and other state-of-the-art models in segmentation accuracy on several medical image datasets..."

"85% of executives said AI is helping increase revenue, and 80% said it’s helping reduce costs."

"We found that shortcut mitigation methods improved classification performance under strong spurious correlations during training."

""Prima is designed to be a co-pilot for medical image interpretation, much like ChatGPT provides email drafts and recommendations.""

"Our model is initially trained on high resolution computational fluid dynamics (CFD) simulations and their downsampled counterparts. It is then fine-tuned on a small, harmonized dataset of paired 4D Flow MRI and CFD samples."

"Extensive experiments on five public benchmarks (Kvasir-SEG, CVC-300, CVC-ColonDB, CVC-Clinic, and PolypGen) demonstrate consistent state-of-the-art performance, with 3-8% Dice improvements and 10-20% higher "

"The proposed method achieves a Dice Similarity Score (DSC) of 0.900 for Whole Tumor (WT) segmentation on the BraTS2021 validation set, demonstrating performance comparable to leading models."

"This study investigates whether machine learning algorithms, specifically convolutional neural networks (CNNs), can detect subtle histological features in WSIs of low-grade tubular adenomas that are predictive of a patient's long-term risk of developing colorectal cancer."

"AI-supported breast cancer screening spots more cancers earlier, landmark trial finds"

""AI hasn’t replaced anyone, it’s just made us more efficient and more valuable.""

"We introduce a method for identifying important visual concepts within large multimodal models (LMMs) and use it to investigate the behaviors these models exhibit when prompted with medical tasks."

"Chinese hospitals are using Alibaba's AI tool "PANDA" to re-examine 180,000 CT scan images and found approximately 24 cases of pancreatic cancer that doctors had overlooked."

""This is really a way to improve an overall screening test," [said lead author, Dr. Kristina Lang]."

"The image-based approach achieved 5-year time-dependent AUCs of 0.64, 0.70, and 0.70, respectively."

"I am able to generate the Lung Mesh but around the lung the torso/skin is also present which I am unable to remove ."

"So I am trying to create meshes from nifti files of Lungs. I am able to create the lung meshes accurately but the problem is along with the lungs there is a torso like skin around tge lungs which I donot want."

"A DANN trained on labeled breast and colon data and adapted to unlabeled lung data reaches 95.56% accuracy."

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

"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."

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

"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."

"The article's context, from ArXiv, suggests it's a research paper."

"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 article's context highlights the use of AI to address the specifics of multi-label long-tail data within an X-ray analysis context."

"The research focuses on segmentation of breast ultrasound images using a novel multimodal approach."

"ASCHOPLEX encounters Dafne: a federated continuous learning project for the generalizability of the Choroid Plexus automatic segmentation"