AIMC Topic: Humans

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Looking at the fringes of MedTech innovation: a mapping review of horizon scanning and foresight methods.

BMJ open
OBJECTIVES: Horizon scanning (HS) is a method used to examine signs of change and may be used in foresight practice. HS methods used for the identification of innovative medicinal products cannot be applied in medical technologies (MedTech) due to di...

Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials.

BMJ open
OBJECTIVES: Numbers of research have reported the usage of robot-assisted gait training for walking restoration post-stroke. However, no consistent conclusion has been reached yet about the efficacy of exoskeleton robot-assisted training (ERAT) on ga...

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: Experience-based knowledge and value considerations of health professionals, citizens, and patients are essential to formulate public health and clinical guidelines that are relevant and applicable to medical practice. Conventional method...

Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features.

Pancreas
OBJECTIVES: Natural language processing (NLP) algorithms can interpret unstructured text for commonly used terms and phrases. Pancreatic pathologies are diverse and include benign and malignant entities with associated histologic features. Creating a...

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.

PloS one
OBJECTIVES: The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predictive for pathological complete response pCR after Neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC).

Development of an ontology to characterize mental functioning.

Disability and rehabilitation
PURPOSE OF THE ARTICLE: This article describes a conceptual and methodological approach to integrating functional information into an ontology to categorize mental functioning, which to date is an under-developed area of classification, and supports ...

Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Although several studies have shown the usefulness of artificial intelligence to identify abnormalities in small-bowel capsule endoscopy (SBCE) images, few studies have proven its actual clinical usefulness. Thus, the aim of this study wa...

Fully automated sinogram-based deep learning model for detection and classification of intracranial hemorrhage.

Medical physics
PURPOSE: To propose an automated approach for detecting and classifying Intracranial Hemorrhages (ICH) directly from sinograms using a deep learning framework. This method is proposed to overcome the limitations of the conventional diagnosis by elimi...

The Fidelity of Artificial Intelligence to Multidisciplinary Tumor Board Recommendations for Patients with Gastric Cancer: A Retrospective Study.

Journal of gastrointestinal cancer
PURPOSE: Due to significant growth in the volume of information produced by cancer research, staying abreast of recent developments has become a challenging task. Artificial intelligence (AI) can learn, reason, and understand the enormous corpus of l...

Exploring examinees' responses to constructed response items with a supervised topic model.

The British journal of mathematical and statistical psychology
Textual data are increasingly common in test data as many assessments include constructed response (CR) items as indicators of participants' understanding. The development of techniques based on natural language processing has made it possible for re...