AIMC Topic: Humans

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Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

STAR protocols
Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-COVID condition (PCC). Applicable to various diseases, we outline steps for data preprocessing and integrating diverse assay datasets. Then, we detail ...

Attentional decoder networks for chest X-ray image recognition on high-resolution features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This paper introduces an encoder-decoder-based attentional decoder network to recognize small-size lesions in chest X-ray images. In the encoder-only network, small-size lesions disappear during the down-sampling steps or ar...

Residency Application Selection Committee Discriminatory Ability in Identifying Artificial Intelligence-Generated Personal Statements.

Journal of surgical education
OBJECTIVE: Advances in artificial intelligence (AI) have given rise to sophisticated algorithms capable of generating human-like text. The goal of this study was to evaluate the ability of human reviewers to reliably differentiate personal statements...

An evaluation of the xenobotic cognitive project: Towards Stage 1 of xenobotic cognition.

Endeavour
Xenobot, the world's first biological robot, puts numerous philosophical riddles before us. One among them pertains to the cognitive status of these entities. Are these biological robots cognitive? To evaluate the cognitive status of xenobots and to ...

One model to use them all: training a segmentation model with complementary datasets.

International journal of computer assisted radiology and surgery
PURPOSE: Understanding surgical scenes is crucial for computer-assisted surgery systems to provide intelligent assistance functionality. One way of achieving this is via scene segmentation using machine learning (ML). However, such ML models require ...

MMSyn: A New Multimodal Deep Learning Framework for Enhanced Prediction of Synergistic Drug Combinations.

Journal of chemical information and modeling
Combination therapy is a promising strategy for the successful treatment of cancer. The large number of possible combinations, however, mean that it is laborious and expensive to screen for synergistic drug combinations in vitro. Nevertheless, becaus...

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study.

Radiography (London, England : 1995)
INTRODUCTION: To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low...

Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis.

Sensors (Basel, Switzerland)
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digita...

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

BMC cancer
BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic fe...

Arrhythmia detection by the graph convolution network and a proposed structure for communication between cardiac leads.

BMC medical research methodology
One of the most common causes of death worldwide is heart disease, including arrhythmia. Today, sciences such as artificial intelligence and medical statistics are looking for methods and models for correct and automatic diagnosis of cardiac arrhythm...