Latest AI and machine learning research in covid-19 for healthcare professionals.
Background: HIV testing is the entry point into the diagnosis, treatment and viral suppression cascade, yet in many low and middle income countries the household surveys used to monitor testing coverage are not powered for estimation below the regional level. We produced calibrated district level estimates of HIV testing uptake among women in Ghana across three Demographic and Health Survey (DHS) ...
L-3,4-dihydroxyphenylalanine (L-Dopa) is an important pharmaceutical for the treatment of Parkinson's disease and a precursor to numerous catechol-containing compounds. The flavin-dependent monooxygenase HpaBC is a promising biocatalyst for microbial L-Dopa production but exhibits limited native activity toward L-tyrosine. Although structure-based machine learning (ML) models have become increasin...
Promptable segmentation foundation models (FMs) such as SAM3 and Medical SAM3 promise few-shot, interactively-specified segmentation for medical imagi...
Object-centric models often produce fragmented masks, boundary leakage, and incorrect region merging. We introduce Similarity-Shift Refinement (SSR), ...
Recent studies develop pixel-level multimodal large language models (MLLMs) that support both Region Segmentation and Region Understanding, extending ...
This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVI...
This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID...
Despite significant advances in image segmentation, even state-of-the-art models produce masks with imperfect boundaries, semantic inconsistencies, an...
Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated da...
Satellite image editing requires spatially precise object-level control, but supervised editing datasets for overhead imagery are costly to build beca...
Industrial anomaly detection and localization are limited by scarce real anomalies and pixel-level annotations, a bottleneck that synthetic image-mask...
Background: Smartphone enabled remote patient monitoring has the potential to complement conventional follow-up in inflammatory arthritis. We previous...
In X-ray CT, metallic objects cause beam hardening, photon starvation, and scattering, leading to projection inconsistency, streaks, dark bands, and s...
DNA encodes biological function across a continuum of sequence scales, from single-nucleotide and motif-level grammar to regulatory neighborhoods, chr...
Affinity reagents such as antibodies are indispensable for interrogating proteins' biological function. Yet they are costly and frequently unreliable,...
Abstract: Compartmental epidemic models conventionally treat the probability of moving between dis ease states as fixed over time, an assumption that ...
Exact deletion from persistent language-model memory depends on how that memory represents a record. Addressable influence can be removed by algebraic...
Standard masked-language-model fine-tuning applies a uniform masking probability across every token position, assuming reconstruction difficulty is po...
Time-varying implicit neural representations (INRs) provide a compact representation of scientific volumes and, for modalities such as dynamic X-ray c...
Federated learning enables multiple institutions to train shared models without exchanging raw clinical EEG data, but it does not fully prevent privac...