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ACPScanner: Prediction of Anticancer Peptides by Integrated Machine Learning Methodologies.

Journal of chemical information and modeling
Novel therapeutic alternatives for cancer treatment are increasingly attracting global research attention. Although chemotherapy remains a primary clinical solution, it often results in significant side effects for patients. In recent years, anticanc...

AutoMolDesigner for Antibiotic Discovery: An AI-Based Open-Source Software for Automated Design of Small-Molecule Antibiotics.

Journal of chemical information and modeling
Discovery of small-molecule antibiotics with novel chemotypes serves as one of the essential strategies to address antibiotic resistance. Although a considerable number of computational tools committed to molecular design have been reported, there is...

Gross failure rates and failure modes for a commercial AI-based auto-segmentation algorithm in head and neck cancer patients.

Journal of applied clinical medical physics
PURPOSE: Artificial intelligence (AI) based commercial software can be used to automatically delineate organs at risk (OAR), with potential for efficiency savings in the radiotherapy treatment planning pathway, and reduction of inter- and intra-obser...

iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides.

Proteomics
With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as e...

AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.

Journal of proteome research
In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postproce...

A Framework for the Evaluation of Human Machine Interfaces of Robot-Assisted Colonoscopy.

IEEE transactions on bio-medical engineering
UNLABELLED: The Human Machine Interface (HMI) of intraluminal robots has a crucial impact on the clinician's performance. It increases or decreases the difficulty of the tasks, and is connected to the users' physical and mental stress.

Human Digital Twin in Industry 5.0: A Holistic Approach to Worker Safety and Well-Being through Advanced AI and Emotional Analytics.

Sensors (Basel, Switzerland)
This research introduces a conceptual framework designed to enhance worker safety and well-being in industrial environments, such as oil and gas construction plants, by leveraging Human Digital Twin (HDT) cutting-edge technologies and advanced artifi...

"KAIZEN" method realizing implementation of deep-learning models for COVID-19 CT diagnosis in real world hospitals.

Scientific reports
Numerous COVID-19 diagnostic imaging Artificial Intelligence (AI) studies exist. However, none of their models were of potential clinical use, primarily owing to methodological defects and the lack of implementation considerations for inference. In t...

Cellular nucleus image-based smarter microscope system for single cell analysis.

Biosensors & bioelectronics
Cell imaging technology is undoubtedly a powerful tool for studying single-cell heterogeneity due to its non-invasive and visual advantages. It covers microscope hardware, software, and image analysis techniques, which are hindered by low throughput ...

Embracing the future-is artificial intelligence already better? A comparative study of artificial intelligence performance in diagnostic accuracy and decision-making.

European journal of neurology
BACKGROUND AND PURPOSE: The integration of artificial intelligence (AI) in healthcare has the potential to revolutionize patient care and clinical decision-making. This study aimed to explore the reliability of large language models in neurology by c...