Pathology

Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations.

The distribution and composition of -regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tis...

Diagnosis using deep-learning artificial intelligence based on the endocytoscopic observation of the esophagus.

BACKGROUND AND AIMS: The endocytoscopic system (ECS) helps in virtual realization of histology and can aid in confirming histological diagnosis in vivo. We propose replacing biopsy-based histology for esophageal squamous cell carcinoma (ESCC) by using the ECS. We applied deep-learning artificial intelligence (AI) to analyse ECS images of the esophagus to determine whether AI can support endoscopis...

Structured illumination microscopy combined with machine learning enables the high throughput analysis and classification of virus structure.

Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools i...

Malaria parasite detection and cell counting for human and mouse using thin blood smear microscopy.

Despite the remarkable progress that has been made to reduce global malaria mortality by 29% in the past 5 years, malaria is still a serious global he...

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 million people worldwide. About 85% of AD cases begin i...

Extending 2-D Convolutional Neural Networks to 3-D for Advancing Deep Learning Cancer Classification With Application to MRI Liver Tumor Differentiation.

Deep learning (DL) architectures have opened new horizons in medical image analysis attaining unprecedented performance in tasks such as tissue classi...

The current role of prostate multiparametric magnetic resonance imaging.

Prostate multi-parametric magnetic resonance imaging (mpMRI) has shown excellent sensitivity for Gleason ≥7 cancers, especially when their volume is ≥...

Incorporating automatically learned pulmonary nodule attributes into a convolutional neural network to improve accuracy of benign-malignant nodule classification.

Existing deep-learning-based pulmonary nodule classification models usually use images and benign-malignant labels as inputs for training. Image attri...

Anticoagulant Related Nephropathy Induced by Dabigatran.

We describe a case of biopsy-proven dabigatran related nephropathy in a patient without underlying IgA nephropathy. To date, dabigatran related nephro...

A deep learning based method for large-scale classification, registration, and clustering of in-situ hybridization experiments in the mouse olfactory bulb.

BACKGROUND: The Allen Mouse Brain Atlas allows study of the brain's molecular anatomy at cellular scale, for thousands genes. To fully leverage this r...

Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance. Pooled miss rates for polyps are as high as 22%, ...

Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developin...

Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis)...

Is Intensity Inhomogeneity Correction Useful for Classification of Breast Cancer in Sonograms Using Deep Neural Network?

The sonogram is currently an effective cancer screening and diagnosis way due to the convenience and harmlessness in humans. Traditionally, lesion bou...

Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton.

BACKGROUND: Phytoplankton species identification and counting is a crucial step of water quality assessment. Especially drinking water reservoirs, bat...

Conversion from tacrolimus to belatacept improves renal function in kidney transplant patients with chronic vascular lesions in allograft biopsy.

BACKGROUND: Conversion from tacrolimus to belatacept has been shown to be beneficial for an increasing number of kidney transplant (KT) patients. Pred...

Patch-based system for Classification of Breast Histology images using deep learning.

In this work, we proposed a patch-based classifier (PBC) using Convolutional neural network (CNN) for automatic classification of histopathological br...

In vitro activity of tedizolid and other comparator drugs in methicillin-resistant Staphylococcus aureus isolates in skin and soft tissue infections in seven Colombian hospitals.

Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) causes severe skin and soft tissue infections in hospitals and, more recently, in the...

Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI.

OBJECTIVE: To investigate the value of machine learning (ML)-based high-dimensional quantitative texture analysis (qTA) on T2-weighted magnetic resona...

Nasal cytology with deep learning techniques.

BACKGROUND: In recent years, cytological observations in the Rhinology field are being increasingly utilized. This development has taken place over th...