AIMC Topic: Deep Learning

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Deep Learning-Aided Noninvasive Monitoring of Skin Tissue Temperature Distribution and Blood Perfusion Rate Based on Fractal Conformal Sensors.

ACS sensors
Skin thermophysical properties are key for health assessment with real-time monitoring enabling early detection of skin-related issues. A polydimethylsiloxane-encapsulated Peano fractal conformal sensor is fabricated by flexible printed circuit techn...

GeoEvoBuilder: A deep learning framework for efficient functional and thermostable protein design.

Proceedings of the National Academy of Sciences of the United States of America
While deep learning has advanced protein sequence and function design, engineering highly active and stable proteins still requires labor-intensive iterative computational design and experimentation. There is a critical need for methods capable of di...

Sustainable deep learning-based breast lesion segmentation: impact of breast region segmentation on performance.

BMC medical imaging
PURPOSE: Segmentation of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is critical for effective diagnosis. This study investigates the impact of breast region segmentation (BRS) on the performance of deep learning-...

AI-based modality-agnostic classification system for vascular calcifications.

Scientific reports
The importance of vascular calcification in major adverse cardiovascular events such as heart attacks or strokes has been established. However, calcifications have heterogeneous phenotypes, and their influence on diseased tissue stability remains poo...

Internet of things enabled indoor activity monitoring for visually impaired people with hybrid deep learning and optimized algorithms for enhanced safety.

Scientific reports
Indoor activity monitoring methods promise the wellbeing and security of elderly and visually challenging individuals living in their homes. These methods use numerous technologies and sensors to monitor daily actions, namely movement, sleep patterns...

Transformer-assisted broad learning for hybrid intelligence-based skin cancer segmentation.

Scientific reports
With the rise of Transformer architectures, deep learning applications have gradually shifted from traditional convolutional neural networks to Transformers based on self-attention mechanisms. In tasks such as image classification, segmentation, and ...

A Multimodal Convolutional Neural Network Model for Parkinson's Disease Diagnosis Based on Fused Handwriting Dynamics Signals.

Journal of medical systems
Parkinson's disease (PD) is a prevalent and complex neurodegenerative disorder, with early diagnosis playing a critical role in timely treatment and management. Handwriting dynamics has emerged as a promising biomarker for early detection of PD, yet ...

Advanced deep learning-based brain tumor classification using a novel customized CNN and optimized residual network.

PloS one
The uncontrollable and rapid growth of brain cells can lead to brain tumors. If left untreated, this condition may result in severe health consequences, including death. Accurate detection and classification are the essential steps toward understandi...

Detection of Hypokalemia, Hyponatremia, and Hyperkalemia in Heart Failure Patients Using Artificial Intelligence Techniques via Electrocardiography.

Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
OBJECTIVE: Detection and monitoring of electrolyte imbalances are essential for the appropriate treatment of many metabolic diseases. However, no reliable and noninvasive tool currently exists for such detection. Electrolyte disorders, particularly i...

ParametrizANI: Fast and Accessible Dihedral Parametrization for Small Molecules.

Journal of chemical information and modeling
In molecular studies, the accurate parametrization of small molecules stands as an essential yet growing demand. Addressing this, we introduce ParametrizANI, a tool crafted explicitly for establishing detailed protocols for dihedral parametrization u...