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Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma.

Cancer
BACKGROUND: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represen...

Robotic Transaxillary Hemithyroidectomy Using the da Vinci SP Robotic System: Initial Experience With 10 Consecutive Cases.

Surgical innovation
Many studies have shown the operative feasibility and safety of robotic thyroidectomy. However, there is still a concern on the operative invasiveness of robotic thyroidectomy owing to the wide flap dissection. The aim of this study was to introduce...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...

Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing.

AJR. American journal of roentgenology
The purpose of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for fully automated quantification of emphysema on chest CT compared with pulmonary function testing (spirometry). A total of 141 patients (72 women...

Factors that affect younger and older adults' causal attributions of robot behaviour.

Ergonomics
Stereotypes are cognitive shortcuts that facilitate efficient social judgments about others. Just as causal attributions affect perceptions of people, they may similarly affect perceptions of technology, particularly anthropomorphic technology such a...

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Nature communications
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral ...

Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.

Scandinavian journal of trauma, resuscitation and emergency medicine
BACKGROUND: In emergency medical services (EMSs), accurately predicting the severity of a patient's medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and validated an...

SeizureBank: A Repository of Analysis-ready Seizure Signal Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment outcomes and quality of life. Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive mea...