AIMC Topic: Humans

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Automated segmentation of 2D low-dose CT images of the psoas-major muscle using deep convolutional neural networks.

Radiological physics and technology
The psoas-major muscle has been reported as a predictive factor of sarcopenia. The cross-sectional area (CSA) of the psoas-major muscle in axial images has been indicated to correlate well with the whole-body skeletal muscle mass. In this study, we e...

Common spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface.

Journal of neuroscience methods
BACKGROUND: Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR)....

Accurate intracellular and in vivo temperature sensing based on CuInS/ZnS QD micelles.

Journal of materials chemistry. B
Accurate and sensitive temperature sensing is of great importance for studying biological activities in cells and tissues. Due to the complexity of the microenvironments, most of the existing thermometry systems cannot meet the needs of accurate intr...

A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.

Medical physics
PURPOSE: This work aims to develop a new framework of image quality assessment using deep learning-based model observer (DL-MO) and to validate it in a low-contrast lesion detection task that involves CT images with patient anatomical background.

Image domain dual material decomposition for dual-energy CT using butterfly network.

Medical physics
PURPOSE: Dual-energy CT (DECT) has been increasingly used in imaging applications because of its capability for material differentiation. However, material decomposition suffers from magnified noise from two CT images of independent scans, leading to...

Bioinspired Hairy Skin Electronics for Detecting the Direction and Incident Angle of Airflow.

ACS applied materials & interfaces
The human skin has inspired multimodal detection using smart devices or systems in fields including biomedical engineering, robotics, and artificial intelligence. Hairs of a high aspect ratio (AR) connected to follicles, in particular, detect subtle ...

Using natural language processing to extract structured epilepsy data from unstructured clinic letters: development and validation of the ExECT (extraction of epilepsy clinical text) system.

BMJ open
OBJECTIVE: Routinely collected healthcare data are a powerful research resource but often lack detailed disease-specific information that is collected in clinical free text, for example, clinic letters. We aim to use natural language processing techn...

QAnalysis: a question-answer driven analytic tool on knowledge graphs for leveraging electronic medical records for clinical research.

BMC medical informatics and decision making
BACKGROUND: While doctors should analyze a large amount of electronic medical record (EMR) data to conduct clinical research, the analyzing process requires information technology (IT) skills, which is difficult for most doctors in China.

Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs.

PLoS computational biology
Increasing evidence has indicated that microRNAs(miRNAs) play vital roles in various pathological processes and thus are closely related with many complex human diseases. The identification of potential disease-related miRNAs offers new opportunities...

Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

Scientific reports
The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied to the relationship between diseases. The study aim was to identify diseases associated with endomet...