AIMC Topic: Deep Learning

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Discovery of a structural class of antibiotics with explainable deep learning.

Nature
The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis. Deep learning approaches have aided in exploring chemical spaces; these typically use black box models and do not provide...

Blood clot and fibrin recognition method for serum images based on deep learning.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Detecting and identifying of clots and fibrins in serum is an important process in the analysis stage before laboratory analysis. Currently, visual examination is commonly employed in clinical laboratories for this purpose. However, this ...

Deep Learning Model for Classifying and Evaluating Soybean Leaf Disease Damage.

International journal of molecular sciences
Soybean ( (L.) Merr.) is a major source of oil and protein for human food and animal feed; however, soybean crops face diverse factors causing damage, including pathogen infections, environmental shifts, poor fertilization, and incorrect pesticide us...

COVID-19 infection segmentation using hybrid deep learning and image processing techniques.

Scientific reports
The coronavirus disease 2019 (COVID-19) epidemic has become a worldwide problem that continues to affect people's lives daily, and the early diagnosis of COVID-19 has a critical importance on the treatment of infected patients for medical and healthc...

Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.

European radiology
OBJECTIVES: To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs.

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data.

Behavior research methods
We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using on...

An intelligent identification and classification system of decoration waste based on deep learning model.

Waste management (New York, N.Y.)
Efficient sorting and recycling of decoration waste are crucial for the industry's transformation, upgrading, and high-quality development. However, decoration waste can contain toxic materials and has greatly varying compositions. The traditional me...

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

European journal of radiology
PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) algorithms have been shown to enable diagnostic image quality at lower radiation doses than iterative ...

Deep-Orga: An improved deep learning-based lightweight model for intestinal organoid detection.

Computers in biology and medicine
PROBLEM: Organoids are 3D cultures that are commonly used for biological and medical research in vitro due to their functional and structural similarity to source organs. The development of organoids can be assessed by morphological tests. However, m...