Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.artmed.2011.04.006 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Correction: Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer.
J Transl Med
January 2025
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangzhou, China.
Risk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy.
BMC Pregnancy Childbirth
January 2025
Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang, 314001, China.
Background: Intrahepatic cholestasis of pregnancy (ICP) is a liver disorder that occurs in the second and third trimesters of pregnancy and is associated with a significant risk of fetal complications, including premature birth and fetal death. In clinical practice, the diagnosis of ICP is predominantly based on the presence of pruritus in pregnant women and elevated serum total bile acid. However, this approach may result in missed or delayed diagnoses.
View Article and Find Full Text PDFAssessment of cardiac iron deposition and genotypic classification in pediatric beta-thalassemia major: the role of cardiac MRI.
BMC Med Imaging
January 2025
Department of Radiology, Shenzhen Children's Hospital, Shantou University Medical College, 7019 Yitian Road, Futian District, Shenzhen, 518038, China.
Background: Beta thalassemia major (β-TM) is a severe genetic anemia with considerable phenotypic heterogeneity. This study investigated whether genotype correlates with distinct myocardial iron overload patterns, assessed by cardiovascular magnetic resonance (CMR) T2* values.
Methods: CMR data for cardiac iron deposition evaluation, which recruited pediatric participants between January 2021 and December 2024, were analyzed with CVI42.
Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives.
Mol Med
January 2025
Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran.
Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somatic alterations leads to a high rate of resistance to current therapies or reduces the efficacy of hematopoietic stem cell transplantation (HSCT), thus increasing the risk of relapse and mortality. Single-cell RNA sequencing (scRNA-seq) will enable the classification of AML and guide treatment approaches by profiling patients with different facets of the same disease, stratifying risk, and identifying new potential therapeutic targets at the time of diagnosis or after treatment.
View Article and Find Full Text PDFDecoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence.
Nat Cancer
January 2025
Institute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, Germany.
Despite advances in precision oncology, clinical decision-making still relies on limited variables and expert knowledge. To address this limitation, we combined multimodal real-world data and explainable artificial intelligence (xAI) to introduce AI-derived (AID) markers for clinical decision support. We used xAI to decode the outcome of 15,726 patients across 38 solid cancer entities based on 350 markers, including clinical records, image-derived body compositions, and mutational tumor profiles.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!