COVID-19

Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning.

To develop a deep learning model using transfer learning for automatic detection and segmentation of neck lymph nodes (LNs) in computed tomography (CT) images, the study included 11,013 annotated LNs with a short-axis diameter ≥ 3 mm from 626 head and neck cancer patients across four hospitals. The nnUNet model was used as a baseline, pre-trained on a large-scale head and neck dataset, and then fi...

Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Development of antibodies often begins with the assessment and optimization of their physicochemical properties, and their efficient engagement with the target of interest. Decisions at the early optimization stage are critical for the success of the drug candidate but are constrained due to the limited knowledge of the antibody and target pharmacology. In the present work, we propose a machine le...

Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper.

Training machine learning models using data from severe COVID-19 patients admitted to a central hospital, where entire wards are specifically dedicate...

The external validity of machine learning-based prediction scores from hematological parameters of COVID-19: A study using hospital records from Brazil, Italy, and Western Europe.

The unprecedented worldwide pandemic caused by COVID-19 has motivated several research groups to develop machine-learning based approaches that aim to...

Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.

Spinal cord injury (SCI) is a severe central nervous system injury without effective therapies. PANoptosis is involved in the development of many dise...

Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.

Chinese Hamster Ovary (CHO) cells are the most widely used cell lines to produce recombinant therapeutic proteins such as monoclonal antibodies (mAbs)...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PS...

Synergistic modeling of hemorrhagic dengue fever: Passive immunity dynamics and time-delay neural network analysis.

Dengue fever poses a formidable epidemiological challenge, particularly for vulnerable groups such as infants. This research paper establishes a mathe...

Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment.

Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improving treatment performance. Supervised deep learning...

Accessible halitosis diagnosis: validating the accuracy of novel AI-based compact VSC measuring instrument.

Halitosis presents a significant global health concern, necessitating the development of precise and efficient testing methodologies owing to the high...

Tumor Cellularity Assessment Using Artificial Intelligence Trained on Immunohistochemistry-Restained Slides Improves Selection of Lung Adenocarcinoma Samples for Molecular Testing.

Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in identifying actionable mutations, but lack of bes...

Self-supervised 3D medical image segmentation by flow-guided mask propagation learning.

Despite significant progress in 3D medical image segmentation using deep learning, manual annotation remains a labor-intensive bottleneck. Self-superv...

F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

PURPOSE: Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer...

Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions.

Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) cu...

The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population-Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis.

BACKGROUND: HIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goa...

Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis mod...

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.

Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high com...

Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.

We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image d...

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma cells in the bone marrow. Despite therapeutic advan...

Deep-Learning-Assisted Digital Fluorescence Immunoassay on Magnetic Beads for Ultrasensitive Determination of Protein Biomarkers.

Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the powerful methods for ultrasensitive determination...