Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Leukemia diagnostics have changed significantly because of the advancements in biosensor technologies that improve the early detection, sensitivity, and point-of-care capabilities. Traditional diagnostic methods have a solid foundation, but they have limitations in how highly invasive they are, their cost, and a significant time lapse in providing results, & lack of smartness/intelligence. This re...
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. These network-based algorithms are attractive because regulatory interactions are fundamentally network-based and there are many tools available for downstream analysis. However, most network-based approaches have two major limitations. First, they are ...
This study investigates the use of quantitative LC-MS/MS-based proteomics and surface-enhanced Raman spectroscopy (SERS) for biomarker detection in cl...
Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations...
Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions ...
INTRODUCTION: Artificial intelligence (AI) is increasingly adopted in digital radiography to enhance workflow efficiency, standardisation and support ...
PURPOSE: Although 16-cm wide-detector CT scanners with prospective ECG-gating enable coronary artery imaging within a single cardiac cycle at a low ra...
The efficient accumulation and uniform distribution of nanomedicine within tumors are critical for achieving therapeutic outcomes. However, convention...
OBJECTIVES: This study aimed to develop a novel radiomic model by incorporating features from both habitat subregions and peritumoral regions to preop...
BACKGROUND: Artificial intelligence (AI) and radiomics are increasingly applied in pediatric neuroradiology to enhance diagnostic precision. However, ...
Recent studies have highlighted the impact of copper-induced cell death (cuproptosis) on cancer progression, prognosis, and treatment, but it remains ...
Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic an...
Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specifi...
This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) derived from fluorodeoxyglucose-positron emission to...
OBJECTIVE: The study aims to develop an artificial intelligence (AI) framework for automatic pressure injury (PI) staging directly from raw clinical i...
The isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immuno...
BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...
PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mortality worldwide, particularly in children, older ...
BACKGROUND: Determination of estrogen receptor (ER) and progesterone receptor (PR) status is critical for breast cancer subtyping and guiding endocrin...
The main cause of cervical cancer emerges from long-term Human Papillomavirus (HPV) infections damaging the cervix. The detection methods produced by ...