AIMC Topic: Algorithms

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Machine learning enabled subgroup analysis with real-world data to inform clinical trial eligibility criteria design.

Scientific reports
Overly restrictive eligibility criteria for clinical trials may limit the generalizability of the trial results to their target real-world patient populations. We developed a novel machine learning approach using large collections of real-world data ...

The Dresden Surgical Anatomy Dataset for Abdominal Organ Segmentation in Surgical Data Science.

Scientific data
Laparoscopy is an imaging technique that enables minimally-invasive procedures in various medical disciplines including abdominal surgery, gynaecology and urology. To date, publicly available laparoscopic image datasets are mostly limited to general ...

Centralized contrastive loss with weakly supervised progressive feature extraction for fine-grained common thorax disease retrieval in chest x-ray.

Medical physics
BACKGROUND: Medical images have already become an essential tool for the diagnosis of many diseases. Thus a large number of medical images are being generated due to the daily routine inspection. An efficient image-based disease retrieval system will...

Accelerating gradient descent and Adam via fractional gradients.

Neural networks : the official journal of the International Neural Network Society
We propose a class of novel fractional-order optimization algorithms. We define a fractional-order gradient via the Caputo fractional derivatives that generalizes integer-order gradient. We refer it to as the Caputo fractional-based gradient, and dev...

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems.

Sensors (Basel, Switzerland)
High-sensitivity early fire detection is an essential prerequisite to intelligent building safety. However, due to the small changes and erratic fluctuations in environmental parameters in the initial combustion phase, it is always a challenging task...

Intelligent Sensors for POI Recommendation Model Using Deep Learning in Location-Based Social Network Big Data.

Sensors (Basel, Switzerland)
Aiming at the problem that the existing Point of Interest (POI) recommendation model in social network big data is difficult to extract deep feature information, a POI recommendation model based on deep learning in social networks and big data is pro...

A Hardware-Friendly High-Precision CNN Pruning Method and Its FPGA Implementation.

Sensors (Basel, Switzerland)
To address the problems of large storage requirements, computational pressure, untimely data supply of off-chip memory, and low computational efficiency during hardware deployment due to the large number of convolutional neural network (CNN) paramete...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

Sensors (Basel, Switzerland)
The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an individual's cardiovascular fitness. A trend is emerging for the development of new machine-learning techniques applied to the automatic process of CPET dat...

Large-Scale Tactile Detection System Based on Supervised Learning for Service Robots Human Interaction.

Sensors (Basel, Switzerland)
In this work, a large-scale tactile detection system is proposed, whose development is based on a soft structure using Machine Learning and Computer Vision algorithms to map the surface of a forearm sleeve. The current application has a cylindrical d...