AIMC Topic: Humans

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Low-contrast lesion detection in neck CT: a multireader study comparing deep learning, iterative, and filtered back projection reconstructions using realistic phantoms.

European radiology experimental
BACKGROUND: Computed tomography (CT) reconstruction algorithms can improve image quality, especially deep learning reconstruction (DLR). We compared DLR, iterative reconstruction (IR), and filtered back projection (FBP) for lesion detection in neck C...

The Picasso's skepticism on computer science and the dawn of generative AI: questions after the answers to keep "machines-in-the-loop".

European radiology experimental
Starting from Picasso's quote ("Computers are useless. They can only give you answers"), we discuss the introduction of generative artificial intelligence (AI), including generative adversarial networks (GANs) and transformer-based architectures such...

A personalized mRNA signature for predicting hypertrophic cardiomyopathy applying machine learning methods.

Scientific reports
Hypertrophic cardiomyopathy (HCM) may lead to cardiac dysfunction and sudden death. This study was designed to develop a HCM signature applying bioinformatics and machine learning methods. Data of HCM and normal tissues were obtained from public data...

Exceptional performance with minimal data using a generative adversarial network for alzheimer's disease classification.

Scientific reports
The classification of Alzheimer's disease (AD) using deep learning models is hindered by the limited availability of data. Medical image datasets are scarce due to stringent regulations on patient privacy, preventing their widespread use in research....

A tactile sensing system capable of recognizing objects based on bioinspired self-sensing soft pneumatic actuator.

Bioinspiration & biomimetics
Tactile sensors play an important role when robots perform contact tasks, such as physical information collection, force or displacement control to avoid collision. For these manipulations, excessive contact may cause damage while poor contact cause ...

Machine learning-based derivation and validation of three immune phenotypes for risk stratification and prognosis in community-acquired pneumonia: a retrospective cohort study.

Frontiers in immunology
BACKGROUND: The clinical presentation of Community-acquired pneumonia (CAP) in hospitalized patients exhibits heterogeneity. Inflammation and immune responses play significant roles in CAP development. However, research on immunophenotypes in CAP pat...

A Comparison of Systematic, Targeted, and Combined Biopsy Using Machine Learning for Prediction of Prostate Cancer Risk: A Multi-Center Study.

Medical principles and practice : international journal of the Kuwait University, Health Science Centre
OBJECTIVES: The aims of the study were to construct a new prognostic prediction model for detecting prostate cancer (PCa) patients using machine-learning (ML) techniques and to compare those models across systematic and target biopsy detection techni...

Green finance growth prediction model based on time-series conditional generative adversarial networks.

PloS one
Climate change mitigation necessitates increased investment in green sectors. This study proposes a methodology to predict green finance growth across various countries, aiming to encourage such investments. Our approach leverages time-series Conditi...

Prognosing post-treatment outcomes of head and neck cancer using structured data and machine learning: A systematic review.

PloS one
BACKGROUND: This systematic review aimed to evaluate the performance of machine learning (ML) models in predicting post-treatment survival and disease progression outcomes, including recurrence and metastasis, in head and neck cancer (HNC) using clin...

Recognition of aggressive driving behavior under abnormal weather based on Convolutional Neural Network and transfer learning.

Traffic injury prevention
OBJECTIVES: Aggressive driving behavior can lead to potential traffic collision risks, and abnormal weather conditions can exacerbate this behavior. This study aims to develop recognition models for aggressive driving under various climate conditions...