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Automation

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A novel automated method for comprehensive renal cast quantification from rat kidney sections using QuPath.

American journal of physiology. Renal physiology
The presence of tubular casts within the kidney serves as an important feature when assessing the degree of renal injury. Quantification of renal tubular casts has been historically difficult due to varying cast morphologies, protein composition, and...

Automatic Pavlov ratio measurement method based on spinal landmarks identification by a deep-learning model.

Medical physics
BACKGROUND: Cervical canal stenosis is one of the important pathogenic factors of cervical spondylosis. The accuracy of the Pavlov ratio measurement is crucial for the diagnosis and treatment of cervical spinal stenosis. Manual measurement is influen...

Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow.

Journal of chemical information and modeling
Machine learning (ML) methods provide a pathway to accurately predict molecular properties, leveraging patterns derived from structure-property relationships within materials databases. This approach holds significant importance in drug discovery and...

Automated feature selection for early keratoconus screening optimization.

Biomedical physics & engineering express
In this paper, an automated feature selection (FS) method is presented to optimize machine learning (ML) models' performances, enhancing early keratoconus screening. A total of 448 parameters were analyzed from a dataset comprising 3162 observations ...

Cooperative control of self-learning traffic signal and connected automated vehicles for safety and efficiency optimization at intersections.

Accident; analysis and prevention
Cooperative control of intersection signals and connected automated vehicles (CAVs) possess the potential for safety enhancement and congestion alleviation, facilitating the integration of CAVs into urban intelligent transportation systems. This rese...

Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.

Medical physics
BACKGROUND: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiotherapy (MRgRT) are time-consuming. Conventional population models for deep learning auto-segmentation might be suboptimal for MRgRT at MR-Linacs since the...

ProtChat: An AI Multi-Agent for Automated Protein Analysis Leveraging GPT-4 and Protein Language Model.

Journal of chemical information and modeling
Large language models (LLMs) have transformed natural language processing, enabling advanced human-machine communication. Similarly, in computational biology, protein sequences are interpreted as natural language, facilitating the creation of protein...

Automatic plan selection using deep network-A prostate study.

Medical physics
BACKGROUND: Recently, high-dose-rate (HDR) brachytherapy treatment plans generation was improved with the development of multicriteria optimization (MCO) algorithms that can generate thousands of pareto optimal plans within seconds. This brings a shi...

Transformative laboratory medicine enabled by microfluidic automation and artificial intelligence.

Biosensors & bioelectronics
Laboratory medicine provides pivotal medical information through analyses of body fluids and tissues, and thus, it is essential for diagnosis of diseases as well as monitoring of disease progression. Despite its universal importance, the field is cur...

Does road environment aesthetics influence risky driving behavior of autonomous vehicles? An evaluation on road readiness using explainable machine learning and random parameters multinomial logit with heterogeneity.

Accident; analysis and prevention
Aesthetics has always been an advanced requirement in road environment design, because it can provide a pleasant driving experience and guide better driving behavior for human drivers. However, it remains unknown whether aesthetics-based road environ...