AI Medical Compendium Journal:
Laboratory investigation; a journal of technical methods and pathology

Showing 31 to 40 of 40 articles

Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning.

Laboratory investigation; a journal of technical methods and pathology
Cervical cancer is one of the most frequent cancers in women worldwide, yet the early detection and treatment of lesions via regular cervical screening have led to a drastic reduction in the mortality rate. However, the routine examination of screeni...

Artificial intelligence and computational pathology.

Laboratory investigation; a journal of technical methods and pathology
Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The incorporation of scientific research through clinical informatics, including genomics, proteomics, bioin...

A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas.

Laboratory investigation; a journal of technical methods and pathology
Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signature (IS)-based radiomics model to achieve multilayered preoperative diagnosis and prognostic stratific...

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

Laboratory investigation; a journal of technical methods and pathology
As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)popula...

Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies.

Laboratory investigation; a journal of technical methods and pathology
Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for risk stratification and management of patients with fatty liver diseases and in the decision to use donor livers for transplantation. However, patholo...

Deep learning shows the capability of high-level computer-aided diagnosis in malignant lymphoma.

Laboratory investigation; a journal of technical methods and pathology
A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including ...

Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells.

Laboratory investigation; a journal of technical methods and pathology
Bone marrow aspirate (BMA) differential cell counts (DCCs) are critical for the classification of hematologic disorders. While manual counts are considered the gold standard, they are labor intensive, time consuming, and subject to bias. A reliable a...

Deep learning assisted mitotic counting for breast cancer.

Laboratory investigation; a journal of technical methods and pathology
As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, th...

Microvascularity detection and quantification in glioma: a novel deep-learning-based framework.

Laboratory investigation; a journal of technical methods and pathology
Microvascularity is highly correlated with the grading and subtyping of gliomas, making this one of its most important histological features. Accurate quantitative analysis of microvessels is helpful for the development of a targeted therapy for anti...

Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy.

Laboratory investigation; a journal of technical methods and pathology
Accumulation of abnormal tau in neurofibrillary tangles (NFT) occurs in Alzheimer disease (AD) and a spectrum of tauopathies. These tauopathies have diverse and overlapping morphological phenotypes that obscure classification and quantitative assessm...