AIMC Topic: Deep Learning

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Deep learning models for improving Parkinson's disease management regarding disease stage, motor disability and quality of life.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Motor diagnosis, monitoring and management of Parkinson's disease (PD) focuses mainly on observational methods and, clinical scales, resulting in a subjective evaluation. Inertial sensors combined with artificial intelligenc...

Recent Advances in Structured Illumination Microscopy: From Fundamental Principles to AI-Enhanced Imaging.

Small methods
Structured illumination microscopy (SIM) has emerged as a pivotal super-resolution technique in biological imaging. This review aims to introduce the fundamental principles of SIM, primarily focuses on the latest developments in super-resolution SIM ...

Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images.

Current medical science
OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.

Harnessing Transfer Deep Learning Framework for the Investigation of Transition Metal Perovskite Oxides with Advanced p-n Transformation Sensing Performance.

ACS sensors
Gas sensing materials based on transition metal perovskite oxides (TMPOs) have garnered extensive attention across various fields such as air quality control, environmental monitoring, healthcare, and national defense security. To overcome challenges...

Bidirectional Long Short-Term Memory (BiLSTM) Neural Networks with Conjoint Fingerprints: Application in Predicting Skin-Sensitizing Agents in Natural Compounds.

Journal of chemical information and modeling
Skin sensitization, or allergic contact dermatitis, represents a critical end point in toxicity assessment, with profound implications for drug safety and regulatory decision-making. This study aims to develop a robust deep-learning-based quantitativ...

Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...

Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol.

World journal of emergency surgery : WJES
BACKGROUND: Mild acute biliary pancreatitis (MABP) presents significant clinical and economic challenges due to its potential for relapse. Current guidelines advocate for early cholecystectomy (EC) during the same hospital admission to prevent recurr...

An intelligent framework for skin cancer detection and classification using fusion of Squeeze-Excitation-DenseNet with Metaheuristic-driven ensemble deep learning models.

Scientific reports
Skin cancer is the most dominant and critical method of cancer, which arises all over the world. Its damaging effects can range from disfigurement to major medical expenditures and even death if not analyzed and preserved timely. Conventional models ...

Quantitative analysis and evaluation of winter and summer landscape colors in the Yangzhou ancient Canal utilizing deep learning.

Scientific reports
Color is an important index for human visual evaluation of landscape, and it is also a key factor affecting people's recognition and experience of heritage landscape. In this study, five important sites of the Yangzhou Grand Canal were selected for t...