AIMC Topic: Humans

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Enhancing the diagnostic accuracy of colorectal cancer through the integration of serum tumor markers and hematological indicators with machine learning algorithms.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
BACKGROUND: Colorectal cancer has a high incidence and mortality rate due to a low rate of early diagnosis. Therefore, efficient diagnostic methods are urgently needed.

Virtual Clinical Trials: Implications of Computer Simulations and Artificial Intelligence for Musculoskeletal Research.

The Journal of bone and joint surgery. American volume
In silico clinical trials, particularly when augmented with artificial intelligence methods, represent an innovative approach with much to offer, particularly in the musculoskeletal field. They are a cost-effective, efficient, and ethical means of ev...

Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.

Annals of medicine
BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of concentrated red blood cells due to preoperative anemia or surgical blood loss. However, the use of perioperative blood products increases the risk of ad...

"How I would like AI used for my imaging": children and young persons' perspectives.

European radiology
OBJECTIVES: Artificial intelligence (AI) tools are becoming more available in modern healthcare, particularly in radiology, although less attention has been paid to applications for children and young people. In the development of these, it is critic...

Triplet-aware graph neural networks for factorized multi-modal knowledge graph entity alignment.

Neural networks : the official journal of the International Neural Network Society
Multi-Modal Entity Alignment (MMEA), aiming to discover matching entity pairs on two multi-modal knowledge graphs (MMKGs), is an essential task in knowledge graph fusion. Through mining feature information of MMKGs, entities are aligned to tackle the...

Predicting State-Level Firearm Suicide Rates: A Machine Learning Approach Using Public Policy Data.

American journal of preventive medicine
INTRODUCTION: Over 40,000 people die by suicide annually in the U.S., and firearms are the most lethal suicide method. There is limited evidence on the effectiveness of many state-level policies on reducing firearm suicide. The objective of this stud...

Predicting daily recovery during long-term endurance training using machine learning analysis.

European journal of applied physiology
PURPOSE: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, s...

VascuConNet: an enhanced connectivity network for vascular segmentation.

Medical & biological engineering & computing
Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber bundle segmentation. Enhancing the continuity of segmentation outcomes represents a pivotal challenge ...

Cluster-CAM: Cluster-weighted visual interpretation of CNNs' decision in image classification.

Neural networks : the official journal of the International Neural Network Society
Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision...

Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory.

Neural networks : the official journal of the International Neural Network Society
The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating s...