AI Medical Compendium Topic

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Innovative Approaches to Gender Classification through Unsupervised Machine Learning and Multi-Activity Fusion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In the last decade, gender recognition has garnered significant attention for its diverse applications in healthcare, sports, rehabilitation, and wearable electronics. This study offers a wearable sensor device to record various activities using iner...

Dynamic multi-hypergraph structure learning for disease diagnosis on multimodal data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With its superior capability in complex data modeling, hypergraph computation is a powerful tool for many applications. In this work, we propose using hypergraph computation for disease prediction. Hypergraphs allow for the representation of higher-o...

Beyond Dysplasia: Uncovering Structure in Oral Potentially Malignant Diseases with Unsupervised Contrastive Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated cancer diagnosis research often focuses on a binary task - recognize dysplasia and cancer from other lesions. However, other clinical conditions have estimated malignant transformation rates. Grouping these oral potentially malignant diseas...

Multidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified before testing post-stroke robot assisted motor training (RAMT). Pretraining variations, especially sensory-motor differences may also affect the gai...

Discrimination between RA and LA Sinus Rhythms using machine learning approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial fibrillation (AF) is a common cardiac disease that potentially leads to fatal conditions. Machine Learning (ML) classification methods are widely used to distinguish between sinus rhythm and AF for post-ablation rhythms in ECG. However, intrac...

Unsupervised Hybrid Deep Feature Encoder for Robust Feature Learning from Resting-State EEG Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
EEG classification is a challenging task due to the nonstationary nature of EEG data and the covariance shift induced by cross-subject variance. Recently, various machine learning and deep learning models have been developed to learn robust features ...

Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucial in gastrointestinal (GI) cancer prognosis and treatment. In this paper, we present a novel two-stage weakly supervised methodology, leveraging the s...

Point-of-interest recommender model using geo-tagged photos in accordance with imperialist Fuzzy C-means clustering.

PloS one
Although recommender systems (RSs) strive to provide recommendations based on individuals' histories and preferences, most recommendations made by these systems do not utilize location and time-based information. This paper presents a travel recommen...

StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation.

Neural networks : the official journal of the International Neural Network Society
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data samples are often decentralized and Non-Independently Identically Dist...

Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods.

Scientific reports
Climate change and environmental degradation pose a significant threat to the global community. Soil management is one of the critical factors for achieving climate neutrality, as plants and soils together currently absorb approximately 30% of the CO...