AIMC Topic: Deep Learning

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Improved in Silico Identification of Protein-Protein Interactions Using Deep Learning Approach.

IET systems biology
Protein-protein interactions (PPIs) perform significant functions in many biological activities likewise gene regulation, metabolic pathways and signal transduction. The deregulation of PPIs may cause deadly diseases, such as cancer, autoimmune, pern...

Attention-aware Deep Learning Models for Dermoscopic Image Classification for Skin Disease Diagnosis.

Current medical imaging
BACKGROUND: The skin, being the largest organ in the human body, plays a vital protective role. Skin lesions are changes in the appearance of the skin, such as bumps, sores, lumps, patches, and discoloration. If not identified and treated promptly, s...

Deep Learning-Based Image Restoration and Super-Resolution for Fluorescence Microscopy: Overview and Resources.

Methods in molecular biology (Clifton, N.J.)
Fluorescence microscopy is a key method for the visualization of cellular, subcellular, and molecular live-cell dynamics, enabling access to novel insights into mechanisms of health and disease. However, effects like phototoxicity, the fugitive natur...

[Comparison of the Impact of Deep Learning Techniques on Low-noise Head CT Images].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: This study aims to compare the effects of two types of deep learning (DL) techniques on brain CT values, image noise content, and contrast-to-noise ratio (CNR) between white and gray matter in low-noise head CT images, along with adaptive it...

TNFR-LSTM: A Deep Intelligent Model for Identification of Tumour Necroses Factor Receptor (TNFR) Activity.

IET systems biology
Tumour necrosis factors (TNFs) are key players in processes such as inflammation, cancer development, and autoimmune diseases. However, accurately identifying TNFs remains challenging because of their complex interactions with other cytokines. Althou...

ACP-DPE: A Dual-Channel Deep Learning Model for Anticancer Peptide Prediction.

IET systems biology
Cancer is a serious and complex disease caused by uncontrolled cell growth and is becoming one of the leading causes of death worldwide. Anticancer peptides (ACPs), as a bioactive peptide with lower toxicity, emerge as a promising means of effectivel...

Virtual Monochromatic Imaging of Half-Iodine-Load, Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction in Patients with Renal Insufficiency: A Clinical Pilot Study.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: We retrospectively examined image quality (IQ) of thin-slice virtual monochromatic imaging (VMI) of half-iodine-load, abdominopelvic, contrast-enhanced CT (CECT) by dual-energy CT (DECT) with deep learning image reconstruction (DLIR).

Contrastive Neuron Pruning for Backdoor Defense.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recent studies have revealed that deep neural networks (DNNs) are susceptible to backdoor attacks, in which attackers insert a pre-defined backdoor into a DNN model by poisoning a few training samples. A small subset of neurons in DNN is responsible ...

Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Evaluating neurological impairments post-stroke is essential for assessing treatment efficacy and managing subsequent disabilities. Conventional clinical assessment methods depend largely on clinicians' visual and physical evaluations, resulting in c...

[Artificial Intelligence in Dentistry: A Sign of the Times].

Stomatologiia
UNLABELLED: Artificial Intelligence (AI) has emerged as one of the most significant innovations in dentistry, enabling the efficient analysis of large volumes of data and enhancing the quality of diagnosis and treatment.