AIMC Topic: Reproducibility of Results

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A hybrid feature-based patient-to-image registration method for robot-assisted long bone osteotomy.

International journal of computer assisted radiology and surgery
PURPOSE: The purpose of this study is to provide a simple, feasible and effective patient-to-image registration method for robot-assisted long bone osteotomy, which has rarely been systematically reported. The practical requirement is to meet the acc...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

International journal of hematology
This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose methotrexate (HD-MTX) based on machine learning. A total of 205 patients were recruited. Five variables ...

Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal ch...

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations.

Nature communications
Our knowledge of viral host ranges remains limited. Completing this picture by identifying unknown hosts of known viruses is an important research aim that can help identify and mitigate zoonotic and animal-disease risks, such as spill-over from anim...

Quality control stress test for deep learning-based diagnostic model in digital pathology.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Digital pathology provides a possibility for computational analysis of histological slides and automatization of routine pathological tasks. Histological slides are very heterogeneous concerning staining, sections' thickness, and artifacts arising du...

Evaluating Very Deep Convolutional Neural Networks for Nucleus Segmentation from Brightfield Cell Microscopy Images.

SLAS discovery : advancing life sciences R & D
Advances in microscopy have increased output data volumes, and powerful image analysis methods are required to match. In particular, finding and characterizing nuclei from microscopy images, a core cytometry task, remains difficult to automate. While...

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

Histopathology
AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article w...

Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

Life science alliance
SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that...

A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but is limited by variability in interpretation and insensitivity to change. Thus, there is a critical n...

Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

Molecular diversity
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attractive therapeutic target for obesity. Thus, development of DGAT1 inhibitors with novel chemical scaffolds is desired and important in the drug discov...