AIMC Topic: Retrospective Studies

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Artificial Intelligence-Driven Patient Selection for Preoperative Portal Vein Embolization for Patients with Colorectal Cancer Liver Metastases.

Journal of vascular and interventional radiology : JVIR Dec 3, 2024
PURPOSE: To develop a machine learning algorithm to improve hepatic resection selection for patients with metastatic colorectal cancer (CRC) by predicting post-portal vein embolization (PVE) outcomes.
Embolization, Therapeutic Portal Vein Patient-Specific Modeling Liver Regeneration Humans Adult Clinical Decision-Making Machine Learning Colorectal Neoplasms Female Decision Support Techniques Male Reproducibility of Results Liver Neoplasms Retrospective Studies Middle Aged Aged Treatment Outcome Predictive Value of Tests Patient Selection Hepatectomy
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Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers.

Ultrasound in medicine & biology Dec 3, 2024
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...
Lymph Nodes Nomograms Lymphatic Metastasis Axilla Predictive Value of Tests Neoplasm Staging Ultrasonography, Mammary Adult Breast Neoplasms Middle Aged Ultrasonography Machine Learning Retrospective Studies Female Aged Humans
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Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Journal of applied clinical medical physics Dec 3, 2024
PURPOSE: Optimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment p...
Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Algorithms Precision Medicine Retrospective Studies Head and Neck Neoplasms Humans Artificial Intelligence
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Machine learning in predicting cauda equina imaging outcomes- a solution to the problem.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Dec 3, 2024
PURPOSE: Cauda Equina Syndrome (CES) is a rare surgical emergency. The implications for loss of quality of life through delayed management are high, though no clinical symptom is pathognomonic in its diagnosis. We describe how machine learning based ...
Humans Aged Adult Male Middle Aged Magnetic Resonance Imaging Machine Learning Algorithms Retrospective Studies Female Cauda Equina Syndrome Cauda Equina
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Breast radiotherapy planning: A decision-making framework using deep learning.

Medical physics Dec 3, 2024
BACKGROUND: Effective breast cancer treatment planning requires balancing tumor control while minimizing radiation exposure to healthy tissues. Choosing between intensity-modulated radiation therapy (IMRT) and three-dimensional conformal radiation th...
Radiotherapy Planning, Computer-Assisted Radiotherapy, Conformal Radiotherapy Dosage Radiotherapy, Intensity-Modulated Female Breast Neoplasms Deep Learning Decision Making Organs at Risk Humans Retrospective Studies
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Machine learning based on multiplatform tests assists in subtype classification of mature B-cell neoplasms.

British journal of haematology Dec 3, 2024
Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The WHO classification (morphology, immunology, cytogenetics and molecular biology) provides comprehensive diagnostic understandings. However, MBN subtypi...
Mutation Flow Cytometry Bone Marrow High-Throughput Nucleotide Sequencing Immunohistochemistry Lymphoma, B-Cell Neprilysin Lymphoma, Follicular CD5 Antigens Machine Learning Retrospective Studies Leukemia, Lymphocytic, Chronic, B-Cell East Asian People Humans Lymphoma, Mantle-Cell Leukemia, Hairy Cell Waldenstrom Macroglobulinemia
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A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system.

Scientific reports Dec 3, 2024
The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a n...
Aged Male Middle Aged Deep Learning Decision Support Systems, Clinical Triage Emergency Service, Hospital Clinical Deterioration Artificial Intelligence Humans Algorithms Retrospective Studies Electronic Health Records Female
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BD-StableNet: a deep stable learning model with an automatic lesion area detection function for predicting malignancy in BI-RADS category 3-4A lesions.

Physics in medicine and biology Dec 3, 2024
The latest developments combining deep learning technology and medical image data have attracted wide attention and provide efficient noninvasive methods for the early diagnosis of breast cancer. The success of this task often depends on a large amou...
Image Processing, Computer-Assisted Ultrasonography, Mammary Automation Humans Retrospective Studies Female Breast Neoplasms Deep Learning
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Multimodal multiphasic preoperative image-based deep-learning predicts HCC outcomes after curative surgery.

Hepatology (Baltimore, Md.) Dec 2, 2024
BACKGROUND AND AIMS: HCC recurrence frequently occurs after curative surgery. Histological microvascular invasion (MVI) predicts recurrence but cannot provide preoperative prognostication, whereas clinical prediction scores have variable performances...
Prognosis Carcinoma, Hepatocellular Retrospective Studies Taiwan Tomography, X-Ray Computed Neoplasm Recurrence, Local Female Hepatectomy Aged Hong Kong Male Humans Middle Aged Deep Learning Liver Neoplasms
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Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.

Archives of physical medicine and rehabilitation Dec 2, 2024
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).
Walking Wheelchairs Humans Male Spinal Dysraphism Neural Networks, Computer Middle Aged Machine Learning Adolescent Algorithms Child, Preschool Retrospective Studies Child Female Aged Young Adult Adult
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