AIMC Topic: Osteosarcoma
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Multimodal Diagnostic Approach for Osteosarcoma and Bone Callus Using Hyperspectral Imaging and Deep Learning.
Journal of biophotonics
Jun 1, 2025
Distinguishing osteosarcoma from bone callus remains a clinical challenge due to their morphological similarities. This study proposes J-CAN, a multimodal deep learning framework integrating hyperspectral imaging (HSI) and H&E-stained pathology for r...
Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.
Scientific reports
May 19, 2025
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tools is critical for advancing personalized treatment...
Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.
Clinical and experimental medicine
May 9, 2025
While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic and recurrent cases remains limited. Immunotherapy is emerging as a promising alternative. However, th...
Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
May 1, 2025
OBJECTIVE: The objective of this study was to analyze the incidence and overall survival (OS) of osteosarcoma (OSC) and Ewing's sarcoma (EWS) in a pediatric and adolescent population, employing machine learning (ML) and deep learning (DL) models to p...
Quantitative and Morphology-Based Deep Convolutional Neural Network Approaches for Osteosarcoma Survival Prediction in the Neoadjuvant and Metastatic Settings.
Clinical cancer research : an official journal of the American Association for Cancer Research
Jan 17, 2025
PURPOSE: Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep-learning strategies on histology samples to predic...
Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.
Journal of cellular and molecular medicine
Jan 1, 2025
Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and developing mitophagy-based treatments to combat drug resistance remains challenging. Herein, BayeDEM (...
Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes.
Briefings in bioinformatics
Nov 22, 2024
Identification of cancer subtypes is a critical step for developing precision medicine. Most cancer subtyping is based on the analysis of RNA sequencing (RNA-seq) data from patient cohorts using unsupervised machine learning methods such as hierarchi...
Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database.
Medicine
Sep 27, 2024
Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple machine learning (ML) models with the traditional Cox proportional hazards (CoxPH) model in predict...
Combined bioinformatics and machine learning methodologies reveal prognosis-related ceRNA network and propose ABCA8, CAT, and CXCL12 as independent protective factors against osteosarcoma.
Advances in clinical and experimental medicine : official organ Wroclaw Medical University
Aug 1, 2024
BACKGROUND: Aberrant circular RNA (circRNA) acts as an oncogene or suppressor during neoplasm initiation and development. However, the functions of most circRNAs in osteosarcoma (OS) remain unclear.
RNA, Competitive Endogenous
Chemokine CXCL12
ATP-Binding Cassette Transporters
RNA, Circular
Protective Factors
Prognosis
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Biomarkers, Tumor
Osteosarcoma
Computational Biology
Humans
Bone Neoplasms
RNA, Messenger
Machine Learning
MicroRNAs
Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Osteosarcoma is the most common type of bone cancer. The primary means of osteosarcoma diagnosis is through evaluating plain x-rays. Using image analysis techniques, features that clinicians use to diagnose osteosarcoma can be quantified and studied ...
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