AIMC Topic: Neural Networks, Computer

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Large-scale design and refinement of stable proteins using sequence-only models.

PloS one
Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be ...

Generative machine learning for de novo drug discovery: A systematic review.

Computers in biology and medicine
Recent research on artificial intelligence indicates that machine learning algorithms can auto-generate novel drug-like molecules. Generative models have revolutionized de novo drug discovery, rendering the explorative process more efficient. Several...

A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
INTRODUCTION: The current study presents a deep learning framework to determine, in real-time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real cou...

Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art.

Chemico-biological interactions
Artificial intelligence (AI) and machine learning models are today frequently used for classification and prediction of various biochemical processes and phenomena. In recent years, numerous research efforts have been focused on developing such model...

Incremental Ant-Miner Classifier for Online Big Data Analytics.

Sensors (Basel, Switzerland)
Internet of Things (IoT) environments produce large amounts of data that are challenging to analyze. The most challenging aspect is reducing the quantity of consumed resources and time required to retrain a machine learning model as new data records ...

Efficient Violence Detection in Surveillance.

Sensors (Basel, Switzerland)
Intelligent video surveillance systems are rapidly being introduced to public places. The adoption of computer vision and machine learning techniques enables various applications for collected video features; one of the major is safety monitoring. Th...

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification.

Medical image analysis
Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landma...

Deep contrastive learning based tissue clustering for annotation-free histopathology image analysis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Deep convolutional neural networks (CNNs) have yielded promising results in automatic whole slide images (WSIs) processing for digital pathology in recent years. Training supervised CNNs usually requires a large amount of annotated sample...

Quantifying uncertainty in machine learning classifiers for medical imaging.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning (ML) models in medical imaging (MI) can be of great value in computer aided diagnostic systems, but little attention is given to the confidence (alternatively, uncertainty) of such models, which may have significant clinical...

No-Reference Video Quality Assessment Using Multi-Pooled, Saliency Weighted Deep Features and Decision Fusion.

Sensors (Basel, Switzerland)
With the constantly growing popularity of video-based services and applications, no-reference video quality assessment (NR-VQA) has become a very hot research topic. Over the years, many different approaches have been introduced in the literature to ...