AIMC Topic: Humans

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Machine learning based refined differential gene expression analysis of pediatric sepsis.

BMC medical genomics
BACKGROUND: Differential expression (DE) analysis of transcriptomic data enables genome-wide analysis of gene expression changes associated with biological conditions of interest. Such analysis often provides a wide list of genes that are differentia...

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text.

BMC medical informatics and decision making
BACKGROUNDS: Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by differe...

A machine learning approach to optimizing cell-free DNA sequencing panels: with an application to prostate cancer.

BMC cancer
BACKGROUND: Cell-free DNA's (cfDNA) use as a biomarker in cancer is challenging due to genetic heterogeneity of malignancies and rarity of tumor-derived molecules. Here we describe and demonstrate a novel machine-learning guided panel design strategy...

HybridSucc: A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction.

Genomics, proteomics & bioinformatics
As an important protein acylation modification, lysine succinylation (Ksucc) is involved in diverse biological processes, and participates in human tumorigenesis. Here, we collected 26,243 non-redundant known Ksucc sites from 13 species as the benchm...

Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging.

Contrast media & molecular imaging
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications includin...

Instance Transfer Subject-Dependent Strategy for Motor Imagery Signal Classification Using Deep Convolutional Neural Networks.

Computational and mathematical methods in medicine
In the process of brain-computer interface (BCI), variations across sessions/subjects result in differences in the properties of potential of the brain. This issue may lead to variations in feature distribution of electroencephalogram (EEG) across su...

[The use of artificial neural networks to classify the social vulnerability of municipalities in Rio Grande do Norte State, Brazil].

Cadernos de saude publica
The objective was to apply artificial neural networks to classify municipalities (counties) in Rio Grande do Norte State, Brazil, according to their social vulnerability. This was an ecological study using 17 variables that reflected epidemiological,...

Progressive Multiple Sclerosis Transcriptome Deconvolution Indicates Increased M2 Macrophages in Inactive Lesions.

European neurology
Accumulating evidence suggests M2 macrophages contribute to tissue reparation and limit inflammation in multiple sclerosis (MS). However, most studies have focused on murine models without substantial support through human MS observations. The presen...

Mechanics of walking and running up and downhill: A joint-level perspective to guide design of lower-limb exoskeletons.

PloS one
Lower-limb wearable robotic devices can improve clinical gait and reduce energetic demand in healthy populations. To help enable real-world use, we sought to examine how assistance should be applied in variable gait conditions and suggest an approach...

Evaluation of a stand-alone robotic camera holding system: technology that improves laparoscopy.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
INTRODUCTION: In order to perform laparoscopic procedures, a surgeon requires an assistant to hold the camera. Problems with this approach include table crowding leading to poor ergonomics, and miscommunication leading to poor images. AutoLap is a no...