AIMC Topic: Humans

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Automated diagnosis and classification of temporomandibular joint degenerative disease via artificial intelligence using CBCT imaging.

Journal of dentistry
OBJECTIVES: In this study, artificial intelligence (AI) techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.

Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.

Biochimica et biophysica acta. Molecular basis of disease
Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise from various lineages and exhibit complex dynamics. However, effectively targeting DTP cells remains challenging. We used single-cell RNA sequencing (sc...

Enhancing cardiovascular disease classification in ECG spectrograms by using multi-branch CNN.

Computers in biology and medicine
Cardiovascular disease (CVD) is caused by the abnormal functioning of the heart which results in a high mortality rate across the globe. The accurate and early prediction of various CVDs from the electrocardiogram (ECG) is vital for the prevention of...

OCDet: A comprehensive ovarian cell detection model with channel attention on immunohistochemical and morphological pathology images.

Computers in biology and medicine
BACKGROUND: Ovarian cancer is among the most lethal gynecologic malignancy that threatens women's lives. Pathological diagnosis is a key tool for early detection and diagnosis of ovarian cancer, guiding treatment strategies. The evaluation of various...

A robust and generalized framework in diabetes classification across heterogeneous environments.

Computers in biology and medicine
Diabetes mellitus (DM) represents a major global health challenge, affecting a diverse range of demographic populations across all age groups. It has particular implications for women during pregnancy and the postpartum period. The contemporary preva...

Can we rely on machine learning algorithms as a trustworthy predictor for recurrence in high-grade glioma? A systematic review and meta-analysis.

Clinical neurology and neurosurgery
Early prediction of recurrence in high-grade glioma (HGG) is critical due to its aggressive nature and poor prognosis. Distinguishing true recurrence from treatment-related changes, such as radionecrosis, is a major diagnostic challenge. Machine lear...

InterDIA: Interpretable prediction of drug-induced autoimmunity through ensemble machine learning approaches.

Toxicology
Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substantial challenges in predictive toxicology due to its idiosyncratic nature, complex pathogenesis, and diverse clinical manifestations. To address these ...

Gait-to-Gait Emotional Human-Robot Interaction Utilizing Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer.

Sensors (Basel, Switzerland)
The emotional response of robotics is crucial for promoting the socially intelligent level of human-robot interaction (HRI). The development of machine learning has extensively stimulated research on emotional recognition for robots. Our research foc...

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data.

Sensors (Basel, Switzerland)
The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare mana...

Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) using radar technology is becoming increasingly valuable for applications in areas such as smart security systems, healthcare monitoring, and interactive computing. This study investigates the integration of convoluti...