AIMC Topic: Deep Learning

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An informed deep learning model of the Omicron wave and the impact of vaccination.

Computers in biology and medicine
The Omicron (B.1.1.529) variant of SARS-CoV-2 emerged in November 2021 and has since evolved into multiple lineages. Understanding its transmission, vaccine efficacy, and potential for reinfection is crucial. This study examines the dynamics of Omicr...

A stacked ensemble approach for symptom-based monkeypox diagnosis.

Computers in biology and medicine
The recent monkeypox outbreak has raised global health concerns. Caused by a virus, it is characterized by symptoms such as skin lesions. Early detection is critical for treatment and controlling its spread. This study uses advanced machine learning ...

Mental disorder preventing by worry levels detection in social media using deep learning based on psycho-linguistic features: application on the COVID-19 lockdown period.

Computers in biology and medicine
BACKGROUND: The COVID-19 pandemic has had a profound effect on the daily routines of individuals and has influenced various facets of society, including healthcare systems, economy, education, and more. With lockdown and social distancing measures, p...

Linking Symptom Inventories Using Semantic Textual Similarity.

Journal of neurotrauma
An extensive library of symptom inventories has been developed over time to measure clinical symptoms of traumatic brain injury (TBI), but this variety has led to several long-standing issues. Most notably, results drawn from different settings and s...

SapFlower: an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning.

The New phytologist
Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, ou...

Comparison of deep learning models for facial attractiveness assessment on 3D photos.

Journal of dentistry
OBJECTIVES: Convolutional neural networks (CNNs) have demonstrated remarkable success in orthodontics. This study aimed to evaluate the accuracy and precision of several prominent CNN models for evaluating the facial attractiveness in Chinese orthodo...

Explainable transformer-based deep survival analysis in childhood acute lymphoblastic leukemia.

Computers in biology and medicine
BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common type of leukemia among children and adolescents and can be life-threatening. The incidence of new cases has been increasing in recent years. Developing a predictive model to forecast t...

Detection of COVID-19, lung opacity, and viral pneumonia via X-ray using machine learning and deep learning.

Computers in biology and medicine
The COVID-19 pandemic has significantly strained healthcare systems, highlighting the need for early diagnosis to isolate positive cases and prevent the spread. This study combines machine learning, deep learning, and transfer learning techniques to ...

Interpretable deep learning method to predict wound healing progress based on collagen fibers in wound tissue.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The dynamic evolution of collagen fibers during wound healing is crucial for assessing repair progression, guiding clinical treatment, and drug screening. Current quantitative methods analyzing collagen spatial patterns (den...

Deep-learning-assisted medium optimization improves hyaluronic acid production by Streptococcus zooepidemicus.

Journal of bioscience and bioengineering
To improve the efficiency of hyaluronic acid production by Streptococcus zooepidemicus, the growth medium was optimized with a pipeline involving a deep learning (DL) algorithm. To train the DL model, the initial training dataset (OA01-18) was design...