AIMC Topic: Humans

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Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning.

Ultrasonics
Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast t...

Robotic cell processing facility for clinical research of retinal cell therapy.

SLAS technology
The consistent production of high-quality cells in cell therapy highlights the potential of automated manufacturing. Humanoid robots are a useful option for transferring technology to automate human cell cultures. This study evaluated a robotic cell-...

Design and Analysis of an Upper Limb Rehabilitation Robot Based on Multimodal Control.

Sensors (Basel, Switzerland)
To address the rehabilitation needs of upper limb hemiplegic patients in various stages of recovery, streamline the workload of rehabilitation professionals, and provide data visualization, our research team designed a six-degree-of-freedom upper lim...

A Korean emotion-factor dataset for extracting emotion and factors in Korean conversations.

Scientific reports
Humans express their emotions in various ways, such as through facial expressions and voices. In particular, emotions are directly expressed or indirectly implied in the text of utterance. Research on the technology to identify emotions included in h...

Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery.

Scientific reports
The logistics and delivery industry is undergoing a technology-driven transformation, with robotics, drones, and autonomous vehicles expected to play a key role in meeting the growing challenges of last-mile delivery. To understand the public accepta...

Extracting cancer concepts from clinical notes using natural language processing: a systematic review.

BMC bioinformatics
BACKGROUND: Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed...

Development of an MRI-Based Comprehensive Model Fusing Clinical, Radiomics and Deep Learning Models for Preoperative Histological Stratification in Intracranial Solitary Fibrous Tumor.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate preoperative histological stratification (HS) of intracranial solitary fibrous tumors (ISFTs) can help predict patient outcomes and develop personalized treatment plans. However, the role of a comprehensive model based on clinica...

Wife-Mother Role Conflict at the Critical Child-Rearing Stage: A Machine-Learning Approach to Identify What and How Matters in Maternal Depression Symptoms in China.

Prevention science : the official journal of the Society for Prevention Research
Maternal depression (MD) was one of the most prevalent psychiatric problems worldwide. However, it easily remains untreated and misses the best time to prevent the emergence or worsening of major depressive symptoms due to under-observed stigma and t...

Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.

European radiology
OBJECTIVES: To develop a deep learning (DL) for detection of brain metastasis (BM) that incorporates both gradient- and turbo spin-echo contrast-enhanced MRI (dual-enhanced DL) and evaluate it in a clinical cohort in comparison with human readers and...