AIMC Topic: Humans

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Whole Blood vs Serum-Derived Exosomes for Host and Pathogen-Specific Tuberculosis Biomarker Identification: RNA-Seq-Based Machine-Learning Approach.

Biochemical genetics
Mycobacterium tuberculosis (Mtb) remains a leading infectious disease responsible for millions of deaths. RNA sequencing is a rapidly growing technique and a powerful approach to understanding host and pathogen cross-talks via transcriptional respons...

EnDM-CPP: A Multi-view Explainable Framework Based on Deep Learning and Machine Learning for Identifying Cell-Penetrating Peptides with Transformers and Analyzing Sequence Information.

Interdisciplinary sciences, computational life sciences
Cell-Penetrating Peptides (CPPs) are a crucial carrier for drug delivery. Since the process of synthesizing new CPPs in the laboratory is both time- and resource-consuming, computational methods to predict potential CPPs can be used to find CPPs to e...

HDAC3_VS_assistant: cheminformatics-driven discovery of histone deacetylase 3 inhibitors.

Molecular diversity
Histone deacetylase 3 (HDAC3) inhibitors keep significant therapeutic promise for treating oncological, neurodegenerative, and inflammatory diseases. In this work, we developed robust QSAR regression models for HDAC3 inhibitory activity and acute tox...

Improving search strategies in bibliometric studies on machine learning in renal medicine.

International urology and nephrology
This paper evaluated the bibliometric study by Li et al. (Int Urol Nephrol, 2024) on machine learning in renal medicine. Although the study claims to summarize the forefront trends and hotspots in this field, several key issues require further clarif...

Identification of Multi-functional Therapeutic Peptides Based on Prototypical Supervised Contrastive Learning.

Interdisciplinary sciences, computational life sciences
High-throughput sequencing has exponentially increased peptide sequences, necessitating a computational method to identify multi-functional therapeutic peptides (MFTP) from their sequences. However, existing computational methods are challenged by cl...

The role of artificial intelligence in the diagnosis, imaging, and treatment of thoracic empyema.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: The management of thoracic empyema is often complicated by diagnostic delays, recurrence, treatment failures and infections with antibiotic resistant bacteria. The emergence of artificial intelligence (AI) in healthcare, particular...

Consumer views of functional electrical stimulation and robotic exoskeleton in SCI rehabilitation: A mini review.

Artificial organs
BACKGROUND: Functional electrical stimulation (FES) and robotic exoskeletons represent emerging technologies with significant potential for restoring critical physical functions such as standing and walking-functions that are most susceptible after s...

Breath Analyzer for Real-Time Exercise Fat Burning Prediction: Oral and Alveolar Breath Insights with CNN.

ACS sensors
The increasing prevalence of obesity and metabolic disorders has created a significant demand for personalized devices that can effectively monitor fat metabolism. In this study, we developed an advanced breath analyzer system designed to provide rea...

Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.

Emergency radiology
BACKGROUND: Emergency/trauma radiology artificial intelligence (AI) is maturing along all stages of technology readiness, with research and development (R&D) ranging from data curation and algorithm development to post-market monitoring and retrainin...