Rheumatology

Nothing about us without us: involving patient collaborators for machine learning applications in rheumatology.

Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support for therapy selection, and automated interpretation of clinical images. Nevertheless, such data-driven approaches could potentially model noise, or m...

Orthogonal quantification of soluble inducible T-cell costimulator (ICOS) in healthy and diseased human serum.

Inducible T-cell costimulator (ICOS), a homodimeric protein expressed on the surface of activated T-cells, is being investigated as a potential therapeutic target to treat various cancers. Recent studies have reported aberrant increases in the soluble form of ICOS (sICOS) in human serum in disease-state patients, primarily using commercial ELISA kits. However, results from our in-house immunoassay...

Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients with non-small-cell lung cancer (NSCLC), but only s...

A Proteinase 3 Contribution to Juvenile Idiopathic Arthritis-Associated Cartilage Damage.

A full understanding of the molecular mechanisms implicated in the etiopathogenesis of juvenile idiopathic arthritis (JIA) is lacking. A critical role...

Development of a fluorescent immunochromatographic assay based on quantum dots for the detection of fleroxacin.

Fleroxacin (FLE) is a broad-spectrum fluoroquinolone antibiotic widely used in animal husbandry, veterinary medicine and aquaculture. Eating animal-de...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of bacterial infections because its concentration inc...

Experimental and numerical diagnosis of fatigue foot using convolutional neural network.

Fatigue is an essential criterion for physiotherapy in injured athletes. Muscle fatigue mechanism also is a crucial matter in designing a workout prog...

Cisplatin and paclitaxel co-delivery nanosystem for ovarian cancer chemotherapy.

We have designed and developed an effective drug delivery system using biocompatible polymer of poly (ethylene glycol)-polyaspartic acid (mPEG-PAsp) f...

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic myc...

A computational pipeline for data augmentation towards the improvement of disease classification and risk stratification models: A case study in two clinical domains.

Virtual population generation is an emerging field in data science with numerous applications in healthcare towards the augmentation of clinical resea...

5FU encapsulated polyglycerol sebacate nanoparticles as anti-cancer drug carriers.

The majority of anti-cancer drugs fail to reach clinical trials due to their low water solubility. A biocompatible drug delivery system that encapsula...

Anti-transfer learning for task invariance in convolutional neural networks for speech processing.

We introduce the novel concept of anti-transfer learning for speech processing with convolutional neural networks. While transfer learning assumes tha...

Finite-time control of delay switched systems via input anti-bump switching.

This article devotes to the finite-time (FT) input anti-bump switching control (SC) issue for a kind of delay switched systems (DSSs). Our objective i...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Electronic skins that can sense external stimuli have been of great significance in artificial intelligence and smart wearable devices in recent years...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral qua...

Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.

IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; ...

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.

Determining sensitive drugs for a patient is one of the most critical problems in precision medicine. Using genomic profiles of the tumor and drug inf...

Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in Wild-Type Metastatic Colorectal Cancer.

PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastat...

Response to "Reply to 'A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance: Simplifying the diagnosis of complicated diseases.' Has the complicated disease been simplified too much?" Artificial intelligence system is helpful for diagnosis of cutaneous lupus erythematosus.

Intelligent Diagnosis of Thyroid Ultrasound Imaging Using an Ensemble of Deep Learning Methods.

: At present, thyroid disorders have a great incidence in the worldwide population, so the development of alternative methods for improving the diagno...