Results 151 to 160 of about 2,637,088 (356)

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

open access: yesAdvanced Science, EarlyView.
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu   +10 more
wiley   +1 more source

NQO1‐Mediated Anoikis Resistance and Immune Evasion Define a High‐Risk Multi‐Omic Subtype for Precision Management of T1 High‐Grade Bladder Cancer

open access: yesAdvanced Science, EarlyView.
Multi‐omic profiling of T1 high‐grade bladder cancer identifies a high‐risk subtype (T1HG1) driven by NQO1, which couples anoikis resistance with immune evasion. NQO1 orchestrates macrophage–T cell crosstalk suppression via CXCL9 modulation. Pharmacological NQO1 inhibition with skullcapflavone II enhances cisplatin efficacy, representing a promising ...
Bin Guo   +20 more
wiley   +1 more source

A multi-layer annotated corpus for information extraction in Russian clinical NLP. [PDF]

open access: yesFront Artif Intell
Sultangaziyeva A   +4 more
europepmc   +1 more source

Transcriptomic and Neuroimaging Decoding of Brain‐Immune Crosstalk in Thyroid Eye Disease

open access: yesAdvanced Science, EarlyView.
This study employed an imaging transcriptomics framework integrating resting‐state fMRI with Allen Human Brain Atlas transcriptomic data, coupled with peripheral blood RNA sequencing, to decode brain‐immune crosstalk in thyroid eye disease. Frontal, parietal, subcortical, and brainstem regions were identified as key neuroimmune‐ vulnerable regions ...
Haiyang Zhang   +15 more
wiley   +1 more source

Proposal of a procedure to stratify the reidentification risk of medical data: RIMEDA. [PDF]

open access: yesBMC Med Inform Decis Mak
Behre S   +3 more
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

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