AIMC Topic: Humans

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An end-to-end bi-objective approach to deep graph partitioning.

Neural networks : the official journal of the International Neural Network Society Oct 21, 2024
Graphs are ubiquitous in real-world applications, such as computation graphs and social networks. Partitioning large graphs into smaller, balanced partitions is often essential, with the bi-objective graph partitioning problem aiming to minimize both...
Humans Neural Networks, Computer Computer Graphics Algorithms Deep Learning
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Ensemble transformer-based multiple instance learning to predict pathological subtypes and tumor mutational burden from histopathological whole slide images of endometrial and colorectal cancer.

Medical image analysis Oct 21, 2024
In endometrial cancer (EC) and colorectal cancer (CRC), in addition to microsatellite instability, tumor mutational burden (TMB) has gradually gained attention as a genomic biomarker that can be used clinically to determine which patients may benefit...
Endometrial Neoplasms Colorectal Neoplasms Biomarkers, Tumor Humans Mutation Deep Learning Female Image Interpretation, Computer-Assisted
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Decoding wheat contamination through self-assembled whole-cell biosensor combined with linear and non-linear machine learning algorithms.

Biosensors & bioelectronics Oct 21, 2024
The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition parti...
Mycotoxins Fungi Biosensing Techniques Support Vector Machine Least-Squares Analysis Triticum Food Contamination Neural Networks, Computer Machine Learning Algorithms Humans
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For the busy clinical-imaging professional in an AI world: Gaining intuition about deep learning without math.

Journal of medical imaging and radiation sciences Oct 21, 2024
Medical diagnostics comprise recognizing patterns in images, tissue slides, and symptoms. Deep learning algorithms (DLs) are well suited to such tasks, but they are black boxes in various ways. To explain DL Computer-Aided Diagnostic (CAD) results an...
Humans Algorithms Female Deep Learning Education, Medical, Continuing Diagnostic Imaging Breast Neoplasms Diagnosis, Computer-Assisted
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Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review.

Journal of medical imaging and radiation sciences Oct 21, 2024
INTRODUCTION: Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there hav...
Attitude of Health Personnel Radiologists Humans Artificial Intelligence Diagnostic Imaging Radiology
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Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

Genes & genomics Oct 21, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level...
Male Middle Aged Cell Line, Tumor Tumor Microenvironment Biomarkers, Tumor Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Killer Cells, Natural Carcinoma, Hepatocellular Single-Cell Analysis Liver Neoplasms Humans Machine Learning Prognosis Female
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Deep learning prediction of error and skill in robotic prostatectomy suturing.

Surgical endoscopy Oct 21, 2024
BACKGROUND: Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consumi...
Deep Learning Humans Clinical Competence Robotic Surgical Procedures Suture Techniques Reproducibility of Results Prostatectomy Male
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Advancing Anticancer Drug Discovery: Leveraging Metabolomics and Machine Learning for Mode of Action Prediction by Pattern Recognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 21, 2024
A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action (MoA). Metabolomics combined with machine learning allowed to predict MoAs of novel anti-proliferative drug candidates, focusing on human prostate can...
Prostatic Neoplasms Tandem Mass Spectrometry Energy Metabolism Cell Line, Tumor Metabolomics Drug Discovery Chromatography, Liquid Antineoplastic Agents Machine Learning Male Humans
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Multimodal Representation Learning via Graph Isomorphism Network for Toxicity Multitask Learning.

Journal of chemical information and modeling Oct 21, 2024
Toxicity is paramount for comprehending compound properties, particularly in the early stages of drug design. Due to the diversity and complexity of toxic effects, it became a challenge to compute compound toxicity tasks. To address this issue, we pr...
Neural Networks, Computer Machine Learning Humans Deep Learning Drug-Related Side Effects and Adverse Reactions
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Robust machine learning challenge: An AIFM multicentric competition to spread knowledge, identify common pitfalls and recommend best practice.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Oct 21, 2024
PURPOSE: A novel and unconventional approach to a machine learning challenge was designed to spread knowledge, identify robust methods and highlight potential pitfalls about machine learning within the Medical Physics community.
Image Processing, Computer-Assisted Humans Lung Neoplasms Machine Learning
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