AIMC Topic: Peptide Fragments
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Prediction of Incident Atrial Fibrillation in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort Study.
Clinical journal of the American Society of Nephrology : CJASN
Jul 12, 2021
BACKGROUND AND OBJECTIVES: Atrial fibrillation (AF) is common in CKD and associated with poor kidney and cardiovascular outcomes. Prediction models developed using novel methods may be useful to identify patients with CKD at highest risk of incident ...
Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning.
Frontiers in immunology
Feb 10, 2021
The presence of pathogen-specific antibodies in an individual's blood-sample is used as an indication of previous exposure and infection to that specific pathogen (e.g., virus or bacterium). Measurement of the diagnostic antibodies is routinely achie...
Antigen-Antibody Reactions
DNA, Recombinant
HIV Envelope Protein gp160
Hepatitis C Antigens
Serologic Tests
Peptide Fragments
Humans
High-Throughput Nucleotide Sequencing
Epitopes
Hepatitis C Antibodies
Machine Learning
Amino Acid Sequence
DNA Barcoding, Taxonomic
Communicable Diseases
HIV Core Protein p24
Oligonucleotides
Base Sequence
HIV Infections
Genetic Vectors
Hepatitis C
Polymerase Chain Reaction
Peptide Library
HIV Antibodies
AIDS Serodiagnosis
Automatic construction of molecular similarity networks for visual graph mining in chemical space of bioactive peptides: an unsupervised learning approach.
Scientific reports
Oct 22, 2020
The increasing interest in bioactive peptides with therapeutic potentials has been reflected in a large variety of biological databases published over the last years. However, the knowledge discovery process from these heterogeneous data sources is a...
ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations.
Journal of computer-aided molecular design
Sep 23, 2020
A proinflammatory peptide (PIP) is a type of signaling molecules that are secreted from immune cells, which contributes to the first line of defense against invading pathogens. Numerous experiments have shown that PIPs play an important role in human...
Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.
International journal of molecular sciences
Sep 21, 2020
Easily accessible biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), and related neurodegenerative disorders are urgently needed in an aging society to assist early-stage diagnoses. In this study, we aim...
Identifying Phenogroups in patients with subclinical diastolic dysfunction using unsupervised statistical learning.
BMC cardiovascular disorders
Aug 14, 2020
BACKGROUND: Subclinical diastolic dysfunction is a precursor for developing heart failure with preserved ejection fraction (HFpEF); yet not all patients progress to HFpEF. Our objective was to evaluate clinical and echocardiographic variables to iden...
Heart Failure
Ventricular Dysfunction, Left
Natriuretic Peptide, Brain
Asymptomatic Diseases
Diastole
Deep Learning
Cluster Analysis
Unsupervised Machine Learning
Predictive Value of Tests
Peptide Fragments
Aged
Aged, 80 and over
Male
Ventricular Function, Left
Stroke Volume
Echocardiography
Middle Aged
Risk Assessment
Disease Progression
Diagnosis, Computer-Assisted
Humans
Biomarkers
Retrospective Studies
Female
Risk Factors
Phase I trial on robot assisted retinal vein cannulation with ocriplasmin infusion for central retinal vein occlusion.
Acta ophthalmologica
Jul 23, 2020
PURPOSE: To evaluate the safety and feasibility of robot-assisted retinal vein cannulation with Ocriplasmin infusion for central retinal vein occlusion.
Vitrectomy
Catheterization
Fibrinolysin
Retinal Vein
Retinal Vein Occlusion
Humans
Peptide Fragments
Infusions, Intravenous
Male
Prospective Studies
Fundus Oculi
Robotics
Middle Aged
Female
Fluorescein Angiography
Tomography, Optical Coherence
Treatment Outcome
Aged
Follow-Up Studies
Aged, 80 and over
Visual Acuity
Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Mar 26, 2020
A deep learning-based image analysis could improve diagnostic accuracy and efficiency in pathology work. Recently, we proposed a deep learning-based detection algorithm for C4d immunostaining in renal allografts. The objective of this study is to ass...
Prediction of Contact Residues in Anti-HIV Neutralizing Antibody by Deep Learning.
Japanese journal of infectious diseases
Jan 31, 2020
The monoclonal antibody 1C10 targets the V3 loop of HIV-1 and neutralizes a broad range of clade B viruses. However, the mode of interaction between 1C10 and the V3 loop remains unclear because crystallization of 1C10 and the V3 peptide was unsuccess...
Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.
Scientific reports
Jan 14, 2020
Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using ...
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