AIMC Topic: Humans

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Semi-autonomous touch method merging robot's autonomous touch and user-operated touch for improving user experience in robot touch.

Scientific reports
The demand for therapeutic robots to alleviate mental health problems is growing. Studies have shown that people's mental health improves when they are touched. Consequently, therapeutic robots are designed to alleviate stress through robot's autonom...

Identification of profiles associated with conversions between the Alzheimer's disease stages, using a machine learning approach.

Alzheimer's research & therapy
BACKGROUND: The identification of factors involved in the conversion across the different Alzheimer's disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the ...

Prediction of leukemia peptides using convolutional neural network and protein compositions.

BMC cancer
Leukemia is a type of blood cell cancer that is in the bone marrow's blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemia...

Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer.

BMC medical imaging
BACKGROUND: The purpose of this study is to develop and validate the potential value of the deep learning radiomics nomogram (DLRN) based on ultrasound to differentiate mass mastitis (MM) and invasive breast cancer (IBC).

Adopting machine learning to predict ICU delirium.

Neurosurgical review
With neuropsychiatric complications recognized among COVID-19 patients translating into significant morbidity, we explore the current state-of-the-art for auto Machine Learning (ML) to predict ICU delirium among severe COVID-19 patients which has bee...

Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning.

Scientific reports
In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lack of automa...

A data-centric machine learning approach to improve prediction of glioma grades using low-imbalance TCGA data.

Scientific reports
Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guide the dia...

Hybrid framework for membrane protein type prediction based on the PSSM.

Scientific reports
Membrane proteins are considered the major source of drug targets and are indispensable for drug design and disease prevention. However, traditional biomechanical experiments are costly and time-consuming; thus, many computational methods for predict...

Enhancing gait recognition by multimodal fusion of mobilenetv1 and xception features via PCA for OaA-SVM classification.

Scientific reports
Gait recognition has become an increasingly promising area of research in the search for noninvasive and effective methods of person identification. Its potential applications in security systems and medical diagnosis make it an exciting field with w...