AIMC Topic: Humans

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AutoTFCNNY: A multi-instance neural network for enhanced early cancer detection using TCR data.

PloS one
For most cancers, early diagnosis and intervention can significantly improve cure rates and patient survival. Consequently, achieving early and accurate cancer detection has always been a central focus in both medical practice and scientific research...

Translation and validation of the artificial intelligence anxiety scale in German.

PloS one
AIM: Artificial intelligence anxiety refers to fear due to challenges caused by AI-related changes in one's own life. As the first study, our aim was to translate and validate the German version of the Artificial Intelligence Anxiety Scale (AIAS-G). ...

Robust detection of femtogram-level Alzheimer's biomarkers using machine learning-enhanced graphene biosensors.

Biosensors & bioelectronics
Early diagnosis of Alzheimer's disease (AD) requires blood biomarker tests sensitive to femtogram/mL concentrations. Graphene field-effect transistors (GFETs) are promising for this application, but suffer from device-to-device variability and requir...

Multi-omics identification of RNASE6 as an immune regulatory RNA-binding protein associated with melanoma metastasis.

Autoimmunity
BACKGROUND: Cutaneous melanoma is a highly invasive tumor. It enhances metastasis and resistance to immunotherapy immunosuppressive mechanisms. Understanding RNA-binding proteins (RBPs) in melanoma's immune alterations is limited. This study explore...

DeepRNA-Reg: a deep-learning based approach for comparative analysis of CLIP experiments.

RNA biology
DeepRNA-Reg employs advances in deep learning to enable high-fidelity comparative analysis of paired datasets of high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). In a HITS-CLIP experimental paradigm where Ag...

Harnessing machine learning for metagenomic data analysis: trends and applications.

mSystems
Metagenomic sequencing has revolutionized our understanding of microbial ecosystems by enabling high-resolution profiling of microbes across diverse environments. However, the resulting data are high-dimensional, sparse, and noisy, posing challenges ...

Discovering Biomarkers for Asymptomatic Tuberculosis via Olink Proteomics and Machine Learning.

Journal of proteome research
The diagnosis of asymptomatic tuberculosis (TB) remains challenging due to an early disease stage. This study aimed to identify and validate plasma biomarkers for asymptomatic TB by integrating the Olink proteomics with multiple machine learning algo...

Paired snRNA-seq and scRNA-seq analysis of MASLD patients to identify early-stage markers for disease progression.

Hepatology communications
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. Progression from simple metabolic dysfunction-associated steatotic liver (MASL) without necro-inflammation to...

Deciphering the determinants of recombinant protein expression across the human secretome.

Proceedings of the National Academy of Sciences of the United States of America
Protein secretion is an essential process of mammalian cells. In biomanufacturing, this process can be optimized to enhance production yields and biotherapeutic quality. While cell line engineering and bioprocess optimization have yielded high protei...