AIMC Topic: Deep Learning

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A combined deep learning framework for mammalian m6A site prediction.

Cell genomics
N-methyladenosine (m6A) is the most prevalent chemical modification in eukaryotic mRNAs and plays key roles in diverse cellular processes. Precise localization of m6A sites is thus critical for characterizing the functional roles of m6A in various co...

Design of Biocompatible Nanomaterials Using Quasi-SMILES and Recurrent Neural Networks.

ACS applied materials & interfaces
Screening nanomaterials (NMs) with desired properties from the extensive chemical space presents significant challenges. The potential toxicity of NMs further limits their applications in biological systems. Traditional methods struggle with these co...

A Physically Constrained Deep-Learning Fusion Method for Estimating Surface NO Concentration from Satellite and Ground Monitors.

Environmental science & technology
Accurate estimation of atmospheric chemical concentrations from multiple observations is crucial for assessing the health effects of air pollution. However, existing methods are limited by imbalanced samples from observations. Here, we introduce a no...

Understanding ecosystem services of detailed forest and wetland types using remote sensing and deep learning techniques in Northern China.

Journal of environmental management
Spanning both temperate and sub-frigid zones, Northeast China boasts typical boreal forests and abundant wetland resources. Because of these attributes, the region is critically significant for global climate regulation, carbon sequestration, and bio...

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoarthritis (OA). Knee OA is commonly associated with varus deformity, where the alignment of the knee ...

A continuous pursuit dataset for online deep learning-based EEG brain-computer interface.

Scientific data
This dataset is from an EEG brain-computer interface (BCI) study investigating the use of deep learning (DL) for online continuous pursuit (CP) BCI. In this task, subjects use Motor Imagery (MI) to control a cursor to follow a randomly moving target,...

Automatic detection and proximity quantification of inferior alveolar nerve and mandibular third molar on cone-beam computed tomography.

Clinical oral investigations
OBJECTIVES: During mandibular third molar (MTM) extraction surgery, preoperative analysis to quantify the proximity of the MTM to the surrounding inferior alveolar nerve (IAN) is essential to minimize the risk of IAN injury. This study aims to propos...

Bidirectional Long Short-Term Memory-Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches.

JMIR medical informatics
BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. Previous studies have extracted drug information using relevant SNS data. In particular, it is important to de...

An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).

A systematic review on feature extraction methods and deep learning models for detection of cancerous lung nodules at an early stage -the recent trends and challenges.

Biomedical physics & engineering express
Lung cancer is one of the most common life-threatening worldwide cancers affecting both the male and the female populations. The appearance of nodules in the scan image is an early indication of the development of cancer cells in the lung. The Low Do...