COVID-19

Is the generalizability of a developed artificial intelligence algorithm for COVID-19 on chest CT sufficient for clinical use? Results from the International Consortium for COVID-19 Imaging AI (ICOVAI).

OBJECTIVES: Only few published artificial intelligence (AI) studies for COVID-19 imaging have been externally validated. Assessing the generalizability of developed models is essential, especially when considering clinical implementation. We report the development of the International Consortium for COVID-19 Imaging AI (ICOVAI) model and perform independent external validation.

Computational and artificial intelligence-based methods for antibody development.

Due to their high target specificity and binding affinity, therapeutic antibodies are currently the largest class of biotherapeutics. The traditional largely empirical antibody development process is, while mature and robust, cumbersome and has significant limitations. Substantial recent advances in computational and artificial intelligence (AI) technologies are now starting to overcome many of th...

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinica...

A deep learning based dual encoder-decoder framework for anatomical structure segmentation in chest X-ray images.

Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CA...

MT-nCov-Net: A Multitask Deep-Learning Framework for Efficient Diagnosis of COVID-19 Using Tomography Scans.

The localization and segmentation of the novel coronavirus disease of 2019 (COVID-19) lesions from computerized tomography (CT) scans are of great sig...

Automatic segmentation and measurement of pressure injuries using deep learning models and a LiDAR camera.

Pressure injuries are a common problem resulting in poor prognosis, long-term hospitalization, and increased medical costs in an aging society. This s...

Port-Site Metastasis Identified on Prostate-Specific Membrane Antigen-Targeted 18 F-DCFPyL PET/CT After Robot-Assisted Laparoscopic Radical Prostatectomy.

Port-site metastasis is an extremely rare complication following minimally invasive oncologic surgery for prostate cancer. We present the case of a 74...

Deep Learning-based Automatic Diagnosis of Breast Cancer on MRI Using Mask R-CNN for Detection Followed by ResNet50 for Classification.

RATIONALE AND OBJECTIVES: Diagnosis of breast cancer on MRI requires, first, the identification of suspicious lesions; second, the characterization to...

Tongue crack recognition using segmentation based deep learning.

Tongue cracks refer to fissures with different depth and shapes on the tongue's surface, which can characterize the pathological characteristics of sp...

Research on the Application of Artificial Intelligence in Public Health Management: Leveraging Artificial Intelligence to Improve COVID-19 CT Image Diagnosis.

Since the start of 2020, the outbreak of the Coronavirus disease (COVID-19) has been a global public health emergency, and it has caused unprecedented...

MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations.

Protein-protein interactions play a ubiquitous role in biological function. Knowledge of the three-dimensional (3D) structures of the complexes they f...

Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.

The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predict pathological complete response (PCR), residual ...

TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification.

Sentiment classification is a form of data analytics where people's feelings and attitudes toward a topic are mined from data. This tantalizing power ...

Identification of Asymptomatic COVID-19 Patients on Chest CT Images Using Transformer-Based or Convolutional Neural Network-Based Deep Learning Models.

Novel coronavirus disease 2019 (COVID-19) has rapidly spread throughout the world; however, it is difficult for clinicians to make early diagnoses. Th...

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-...

Artificial intelligence-based recognition for variant pathogenicity of BRCA1 using AlphaFold2-predicted structures.

With the surge of the high-throughput sequencing technologies, many genetic variants have been identified in the past decade. The vast majority of the...

Explainable Machine Learning Model to Predict COVID-19 Severity Among Older Adults in the Province of Quebec.

Context: Patients over the age of 65 years are more likely to experience higher severity and mortality rates than other populations from COVID-19. Cli...

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormaliti...

SoftSAR: The New Softer Side of Socially Assistive Robots-Soft Robotics with Social Human-Robot Interaction Skills.

When we think of "soft" in terms of socially assistive robots (SARs), it is mainly in reference to the soft outer shells of these robots, ranging from...

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various cou...