AIMC Topic: Humans

Clear Filters Showing 48101 to 48110 of 95995 articles

Can we predict anti-seizure medication response in focal epilepsy using machine learning?

Clinical neurology and neurosurgery
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning approach based on clinical factors and diffusion tensor imaging (DTI) to predict anti-seizure medication (ASM) response in focal epilepsy. We hypothesized that ASM r...

Ninety-day morbidity of robot-assisted redo surgery for recurrent rectal prolapse, mesh erosion and pelvic pain: lessons learned from 9 years' experience in a tertiary referral centre.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: With increasing follow-up of patients treated with minimally invasive ventral mesh rectopexy (VMR) more redo surgery can be expected for recurrent rectal prolapse, mesh erosion and pelvic pain. The aim of this study is to evaluate the 90-day mor...

Clinical suitability of deep learning based synthetic CTs for adaptive proton therapy of lung cancer.

Medical physics
PURPOSE: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone-beam CT (CBCT) can provide these daily images, but x-ray scattering limits CBCT-image quality and hampers dose calculation...

Advanced Recovery and High-Sensitive Properties of Memristor-Based Gas Sensor Devices Operated at Room Temperature.

ACS sensors
Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental monitoring, artificial intelligence, and inflammatory diagnosis of asthma patients. However, the co...

Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.

Cell reports. Medicine
Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and...

Analysis of Gastrointestinal Acoustic Activity Using Deep Neural Networks.

Sensors (Basel, Switzerland)
Automated bowel sound (BS) analysis methods were already well developed by the early 2000s. Accuracy of ~90% had been achieved by several teams using various analytical approaches. Clinical research on BS had revealed their high potential in the non-...

Monitoring Illegal Tree Cutting through Ultra-Low-Power Smart IoT Devices.

Sensors (Basel, Switzerland)
Forests play a fundamental role in preserving the environment and fighting global warming. Unfortunately, they are continuously reduced by human interventions such as deforestation, fires, etc. This paper proposes and evaluates a framework for automa...

Enhancing unsupervised medical entity linking with multi-instance learning.

BMC medical informatics and decision making
BACKGROUND: A lot of medical mentions can be extracted from a huge amount of medical texts. In order to make use of these medical mentions, a prerequisite step is to link those medical mentions to a medical domain knowledge base (KB). This linkage of...

Combining data augmentation and domain information with TENER model for Clinical Event Detection.

BMC medical informatics and decision making
BACKGROUND: In recent years, with the development of artificial intelligence, the use of deep learning technology for clinical information extraction has become a new trend. Clinical Event Detection (CED) as its subtask has attracted the attention fr...

Drug knowledge discovery via multi-task learning and pre-trained models.

BMC medical informatics and decision making
BACKGROUND: Drug repurposing is to find new indications of approved drugs, which is essential for investigating new uses for approved or investigational drug efficiency. The active gene annotation corpus (named AGAC) is annotated by human experts, wh...