AIMC Topic: Automation
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Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.
Journal of cardiovascular computed tomography
Jan 9, 2025
BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among...
Aortic Valve Stenosis
Aortic Valve
Predictive Value of Tests
Severity of Illness Index
Time Factors
Treatment Outcome
Atrial Function, Left
Computed Tomography Angiography
Transcatheter Aortic Valve Replacement
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Automation
Risk Factors
Aged
Aged, 80 and over
Stroke Volume
Risk Assessment
Male
Ventricular Function, Left
Artificial Intelligence
Retrospective Studies
Female
Humans
Machine learning-based automated waste sorting in the construction industry: A comparative competitiveness case study.
Waste management (New York, N.Y.)
Jan 8, 2025
This article presents a comparative analysis of the circularity and cost-efficiency of two distinct construction material recycling processes: ML-based automated sorting (MLAS) and conventional sorting technologies. Empirical data was collected from ...
A qualitative, quantitative and dosimetric evaluation of a machine learning-based automatic segmentation method in treatment planning for gastric cancer.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jan 7, 2025
PURPOSE: To investigate the performance of a machine learning-based segmentation method for treatment planning of gastric cancer.
Machine Learning for Reaction Performance Prediction in Allylic Substitution Enhanced by Automatic Extraction of a Substrate-Aware Descriptor.
Journal of chemical information and modeling
Jan 2, 2025
Despite remarkable advancements in the organic synthesis field facilitated by the use of machine learning (ML) techniques, the prediction of reaction outcomes, including yield estimation, catalyst optimization, and mechanism identification, continues...
Automatic brake Driver Assistance System based on deep learning and fuzzy logic.
PloS one
Dec 31, 2024
Advanced Driver Assistance Systems (ADAS) aim to automate transportation fully. A key part of this automation includes tasks such as traffic light detection and automatic braking. While indoor experiments are prevalent due to computational demands an...
A novel automated method for comprehensive renal cast quantification from rat kidney sections using QuPath.
American journal of physiology. Renal physiology
Dec 24, 2024
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...
Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).
Physics in medicine and biology
Dec 24, 2024
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...
Automatic Pavlov ratio measurement method based on spinal landmarks identification by a deep-learning model.
Medical physics
Dec 23, 2024
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
Dec 23, 2024
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
Dec 20, 2024
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 ...
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