Preventive Care

Red blood cell classification in lensless single random phase encoding using convolutional neural networks.

Rapid cell identification is achieved in a compact and field-portable system employing single random phase encoding to record opto-biological signatures of living biological cells of interest. The lensless, 3D-printed system uses a diffuser to encode the complex amplitude of the sample, then the encoded signal is recorded by a CMOS image sensor for classification. Removal of lenses in this 3D sens...

[Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future].

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultation and improves the accuracy of congenital heart disease diagnosis. At the present stage, the AI based cardiac auscultation technique mainly focuses ...

Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study.

In this work, we assess how pre-training strategy affects deep learning performance for the task of distinguishing false-recall from malignancy and no...

Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes.

IMPORTANCE: Screening for diabetic retinopathy is recommended for children with type 1 diabetes (T1D) and type 2 diabetes (T2D), yet screening rates r...

Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter.

To adapt and extend an existing typology of vaccine misinformation to classify the major topics of discussion across the total vaccine discourse on T...

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.

BACKGROUND: We examined the potential change in cancer detection when using an artificial intelligence (AI) cancer-detection software to triage certai...

[Artificial intelligence for cancer detection in breast cancer screening].

Artificial intelligence (AI) has the potential to increase quality and efficiency of breast cancer screening. Recent studies have provided comparative...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate sc...

Colon capsule endoscopy versus CT colonography after incomplete colonoscopy. Application of artificial intelligence algorithms to identify complete colonic investigations.

BACKGROUND: Guidelines suggest computed tomography colonography (CTC) following incomplete optical colonoscopy (OC). Colon capsule endoscopies (CCE) h...

Effectiveness of a Deep-learning Polyp Detection System in Prospectively Collected Colonoscopy Videos With Variable Bowel Preparation Quality.

BACKGROUND: Colonoscopy is the gold standard for polyp detection, but polyps may be missed. Artificial intelligence (AI) technologies may assist in po...

Using Computer-Aided Polyp Detection During Colonoscopy.

Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening.

Chest radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditions. Machine learning based automated solutions ar...

Artificial Intelligence for Understanding Imaging, Text, and Data in Gastroenterology.

Artificial intelligence (AI) could change the practice of gastroenterology through its ability to both acquire and analyze information with speed, rep...

[Application of convolutional neural network to risk evaluation of positive circumferential resection margin of rectal cancer by magnetic resonance imaging].

To explore the feasibility of using faster regional convolutional neural network (Faster R-CNN) to evaluate the status of circumferential resection m...

Machine Learning Assisted Citation Screening for Systematic Reviews.

Evidence-based practice is highly dependent upon up-to-date systematic reviews (SR) for decision making. However, conducting and updating systematic r...

Glaucoma screening: where are we and where do we need to go?

PURPOSE OF REVIEW: Current recommendations for glaucoma screening are decidedly neutral. No studies have yet documented improved long-term outcomes fo...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

The cost-effectiveness of targeted delinquency prevention programs for children depends on the accuracy of the screening process. Screening accuracy i...

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks.

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines a...

Machine Learning Models Improve the Diagnostic Yield of Peripheral Blood Flow Cytometry.

OBJECTIVES: Peripheral blood flow cytometry (PBFC) is useful for evaluating circulating hematologic malignancies (HM) but has limited diagnostic value...

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning p...