AIMC Topic: Neural Networks, Computer

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SUnet: A multi-organ segmentation network based on multiple attention.

Computers in biology and medicine
Organ segmentation in abdominal or thoracic computed tomography (CT) images plays a crucial role in medical diagnosis as it enables doctors to locate and evaluate organ abnormalities quickly, thereby guiding surgical planning, and aiding treatment de...

EGeRepDR: An enhanced genetic-based representation learning for drug repurposing using multiple biomedical sources.

Journal of biomedical informatics
MOTIVATION: Drug repurposing (DR) is an imminent approach for identifying novel therapeutic indications for the available drugs and discovering novel drugs for previously untreatable diseases. Nowadays, DR has major attention in the pharmaceutical in...

Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.

Sensors (Basel, Switzerland)
Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Counseling is the most effective during hospital visits, and the side effects of drugs can be burdensome. Patient empowerment is crucial for understandin...

Interpreting deep learning models for glioma survival classification using visualization and textual explanations.

BMC medical informatics and decision making
BACKGROUND: Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important image features and the model pr...

An empirical comparison of deep learning explainability approaches for EEG using simulated ground truth.

Scientific reports
Recent advancements in machine learning and deep learning (DL) based neural decoders have significantly improved decoding capabilities using scalp electroencephalography (EEG). However, the interpretability of DL models remains an under-explored area...

Deep learning tools to accelerate antibiotic discovery.

Expert opinion on drug discovery
INTRODUCTION: As machine learning (ML) and artificial intelligence (AI) expand to many segments of our society, they are increasingly being used for drug discovery. Recent deep learning models offer an efficient way to explore high-dimensional data a...

The impact of thermal insulating materials in heat loss control in smart green buildings using experimental and swarm intelligent analysis.

Environmental science and pollution research international
The efficacy of saving energy standards depends on the ability to anticipate the heat loss of buildings. Environmentally friendly materials, also known as eco-friendly or sustainable materials, have a minimal negative impact on the environment throug...

Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging.

International journal of medical informatics
BACKGROUND: Precise categorization of pressure injury (PI) stages is critical in determining the appropriate treatment for wound care. However, the expertise necessary for PI staging is frequently unavailable in residential care settings.

Turing and von Neumann machines: Completing the new mechanism.

Bio Systems
Turing (1937) introduces a model of code that is followed by other pioneers of computing machines (such as Flowers 1983, Eckert, Mauchly, Brainerd 1945 and others). One of them is John von Neumann, who defines the concept of optimal code in the conte...

Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information.

Journal of computer-aided molecular design
In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty...