Pathology

Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma.

SIGNIFICANCE: Raman spectroscopy (RS) provides an automated approach for assisting Mohs micrographic...

Artificial intelligence: Emerging player in the diagnosis and treatment of digestive disease.

Given the breakthroughs in key technologies, such as image recognition, deep learning and neural net...

[Recent advances in diagnosis of pulmonary nodule].

With the popularization of health screening and the widespread use of low-dose computed tomography, ...

Optical bone densitometry robust to variation of soft tissue using machine learning techniques: validation by Monte Carlo simulation.

SIGNIFICANCE: To achieve early detection of osteoporosis, a simple bone densitometry method using op...

[Two Cases of Robot-Assisted Total Pelvic Exenteration and Intracorporeal Ileal Conduit for Locally Advanced Rectal Cancer].

We describe two cases of locally advanced rectal cancer (LARC) treated with robot-assisted total pel...

Senhance robot-assisted adrenalectomy: a case series.

We present a case series of 12 consecutive robot-assisted adrenalectomies performed from May 2019 to...

Multi-scale deep learning for the imbalanced multi-label protein subcellular localization prediction based on immunohistochemistry images.

MOTIVATION: The development of microscopic imaging techniques enables us to study protein subcellula...

"White bile" as a result of a malignant bile obstruction.

An 87-year-old female was admitted for endoscopic retrograde cholangiopancreatography (ERCP) due to ...

[Clinical application of Da Vinci robot Xi system in subtotal colorectal resection and natural orifice specimen extraction with single anastomosis].

Machine learning on thyroid disease: a review.

This study reviews the recent progress of machine learning for the early diagnosis of thyroid diseas...

Single-shot hyperspectral imaging based on dual attention neural network with multi-modal learning.

Hyperspectral imaging is being extensively investigated owing to its promising future in critical ap...

SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images.

With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular map of h...

Robot-Assisted Laparoscopic Distal Ureteroureterostomy for Distal Benign Ureteral Strictures with Long-Term Follow-Up.

To demonstrate feasibility of robot-assisted laparoscopic (RAL) ureteroureterostomy (UU) for benign...

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future.

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence ...

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer.

To investigate the correlations between ultrasonographic morphological characteristics quantitativel...

High-throughput single-cell RNA-seq data imputation and characterization with surrogate-assisted automated deep learning.

Single-cell RNA sequencing (scRNA-seq) technologies have been heavily developed to probe gene expres...

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fi...

[Next-generation diagnostic pathology].

With the technological progresses and applications of human genome sequencing, bioinformatics analys...

scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Previous studies on enhancers and their target genes were largely based on bulk samples that represe...

Histopathologic and Machine Deep Learning Criteria to Predict Lymphoma Transformation in Bone Marrow Biopsies.

CONTEXT.—: Large cell transformation (LCT) of indolent B-cell lymphomas, such as follicular lymphoma...

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona...