Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Frozen encoders are chosen by how well a lightweight head reads a finding from their features, not whether the geometry separates it. Nearest-neighbor discordance does, but with unequal banks the opposite-label neighbor wins on density, not geometry, so prevalence alone makes an uninformed encoder look blind. We introduce CANDOR, a discordance measure whose equal-size banks are symmetric under a l...
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual tokenizers can discard fine textures and structural details, while separate representation and diffusion training creates a mismatch between reconstruction and generation objectives. These limitations have renewed interest in pixel-space diffusion, wh...
Standard evaluation of many recognition systems contains distribution shift by construction, since benchmarks place disjoint conditions in the trainin...
3D CT vision-language models (VLMs) classify abnormalities from text prompts in a zero-shot manner, enabling cross-institution deployment where labels...
Cardiometabolic diseases remain among the most persistent drivers of preventable morbidity because diabetes, hypertension, and cardiovascular disease ...
Due to the optical diffraction limit and long imaging distances, Closely-Spaced Infrared Small Targets (CSIST) typically exhibit energy overlap, manif...
Quantum continual learning aims to train quantum models on sequential tasks without losing previously learned knowledge. However, variational quantum ...
Malaria remains a severe health problem in endemic regions because people lack adequate diagnostic tools, leading to delayed medical care and elevated...
Abstract Background: Remote clinical reviews have become an integral component of contemporary nursing practice across community and acute care settin...
Rich internal representations of musical structure are essential for music understanding tasks such as machine-assisted music co-writing, yet self-sup...
Distribution shift in medical imaging remains a central bottleneck for the clinical translation of medical AI. Failure to address it can lead to sever...
As recommender systems mature in the past few years, their optimization objectives have evolved from a primary focusing on short-term behavioral signa...
Brain tumor progression exhibits spatially heterogeneous growth, patient-specific treatment response, and complex interactions with surrounding anatom...
Real-time N-1 contingency screening in an energy management system trades assurance against cost: verifying every credible outage with full power flow...
Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incremen...
Visual generation is increasingly ubiquitous in diverse domains, from text-to-image/video synthesis to multimodal interactive creation. Yet prevailing...
Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without ...
Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabili...
Diffusion models have become the central backbone for modern image, video, and audio generation, but their efficient service remains a challenge. Unli...
Background: Documentation burden significantly impacts nursing workload and well-being, with nurses spending an estimated 20-40% of their time on docu...