AIMC Topic: Humans

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Academic Emotion Classification and Recognition Method for Large-scale Online Learning Environment-Based on A-CNN and LSTM-ATT Deep Learning Pipeline Method.

International journal of environmental research and public health
Subjective well-being is a comprehensive psychological indicator for measuring quality of life. Studies have found that emotional measurement methods and measurement accuracy are important for well-being-related research. Academic emotion is an emoti...

Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival.

The AAPS journal
Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to...

Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data.

Scientific reports
Cell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (ML) have been playing a pivotal role in revolutionizing medical diagnostics. This research presents ...

Deep-learning- and pharmacophore-based prediction of RAGE inhibitors.

Physical biology
The receptor for advanced glycation end products (RAGE) has been identified as a therapeutic target in a host of pathological diseases, including Alzheimer's disease. RAGE is a target with no crystallographic data on inhibitors in complex with RAGE, ...

Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD.

NeuroImage. Clinical
BACKGROUND: Those with autism spectrum disorder (ASD) and/or attention-deficit-hyperactivity disorder (ADHD) exhibit symptoms of hyperactivity and inattention, causing significant hardships for families and society. A potential mechanism involved in ...

Deeply self-supervised contour embedded neural network applied to liver segmentation.

Computer methods and programs in biomedicine
OBJECTIVE: Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images.

Performance Evaluation of Convolutional Neural Network for Hand Gesture Recognition Using EMG.

Sensors (Basel, Switzerland)
Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still ins...

Novel deep neural network based pattern field classification architectures.

Neural networks : the official journal of the International Neural Network Society
Field classification is a new extension of traditional classification frameworks that attempts to utilize consistent information from a group of samples (termed fields). By forgoing the independent identically distributed (i.i.d.) assumption, field c...

SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction.

Neural networks : the official journal of the International Neural Network Society
Complex network is a general model to represent the interactions within technological, social, information, and biological interaction. Often, the direct detection of the interaction relationship is costly. Thus, network structure reconstruction, the...

Attitudes of Patients and Their Relatives Toward Artificial Intelligence in Neurosurgery.

World neurosurgery
BACKGROUND: Artificial intelligence (AI) may favorably support surgeons but can result in concern among patients and their relatives. The aim of this study was to evaluate attitudes of patients and their relatives regarding use of AI in neurosurgery.