AIMC Topic: Neural Networks, Computer

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Leveraging Convolutional Neural Networks for Predicting Symptom Escalation in Chemotherapy Patients: A Temporal Resampling Approach.

Studies in health technology and informatics
This paper introduces a novel approach for predicting symptom escalation in chemotherapy patients by leveraging Convolutional Neural Networks (CNNs). Accurate forecasting of symptom escalation is crucial in cancer care, as it enables timely intervent...

Validation of a Microfluidic Device Prototype for Cancer Detection and Identification: Circulating Tumor Cells Classification Based on Cell Trajectory Analysis Leveraging Cell-Based Modeling and Machine Learning.

International journal for numerical methods in biomedical engineering
Microfluidic devices (MDs) present a novel method for detecting circulating tumor cells (CTCs), enhancing the process through targeted techniques and visual inspection. However, current approaches often yield heterogeneous CTC populations, necessitat...

A WaveNet-based model for predicting the electroglottographic signal from the acoustic voice signal.

The Journal of the Acoustical Society of America
The electroglottographic (EGG) signal offers a non-invasive approach to analyze phonation. It is known, if not obvious, that the onset of vocal fold contacting has a substantial effect on how the vocal folds vibrate and on the quality of the voice. G...

Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.

Clinical transplantation
BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to diagnose GF are limited, ranging from procedural-related complications to low accuracy. With recent...

A Neural Network Finite Element Trileaflet Heart Valve Model Incorporating Multi-Body Contact.

International journal for numerical methods in biomedical engineering
The use of patient-specific computational modeling of cardiovascular diseases has become increasingly popular to improve patient standard of care. Most simulation approaches currently utilize the finite element method (FEM), which is very well establ...

g-Distance: On the comparison of model and human heterogeneity.

Psychological review
Models are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, -di...

Mushroom species classification and implementation based on improved MobileNetV3.

Journal of food science
Current methods for mushroom species classification face limitations in generalization ability and lack exploration of model deployment. To address these issues, this study systematically compares five models, including Transformer and common convolu...

NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction.

Chemical biology & drug design
Sirtuins, a class of NAD+ -dependent deacetylases, play a key role in aging, metabolism, and longevity. Their interaction with NAD+ at the catalytic site is crucial for function, but experimental methods to map NAD+ binding sites are time consuming. ...

Snapshot artificial intelligence-determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) is poised to transform point-of-care practice by providing rapid snapshots of cardiac functioning. Although previous AI models have been developed to estimate left ventricular ejection fraction (LVEF), they ha...

Artificial Intelligence Predicts Fitzpatrick Skin Type, Pigmentation, Redness, and Wrinkle Severity From Color Photographs of the Face.

Journal of cosmetic dermatology
BACKGROUND: Due to high patient demand, increasing numbers of non-dermatologists are performing skin assessments and carrying out laser interventions in medical spas, leading to inferior outcomes and higher complications. A machine learning tool that...