Results 201 to 210 of about 11,426,298 (383)

Machine learning driven biomarker selection for medical diagnosis. [PDF]

open access: yesPLoS One
Bavikadi D   +6 more
europepmc   +1 more source

On The Potential of Image Moments for Medical Diagnosis. [PDF]

open access: yesJ Imaging, 2023
Di Ruberto C, Loddo A, Putzu L.
europepmc   +1 more source

Integrative miRNOMe profiling reveals the miR‐195‐5p–CHEK1 axis and its impact on luminal breast cancer outcomes

open access: yesMolecular Oncology, EarlyView.
In luminal (ER+) breast carcinoma (BC), miRNA profiling identified miR‐195‐5p as a key regulator of proliferation that targets CHEK1, CDC25A, and CCNE1. High CHEK1 expression correlates with worse relapse‐free survival after chemotherapy, especially in patients with luminal A subtype.
Veronika Boušková   +14 more
wiley   +1 more source

Retrieval Augmented Medical Diagnosis System. [PDF]

open access: yesBiol Methods Protoc
Johnson ET, Bande JK, Thomas J.
europepmc   +1 more source

The challenge of cognitive science for medical diagnosis. [PDF]

open access: yesCogn Res Princ Implic, 2023
Croskerry P, Campbell SG, Petrie DA.
europepmc   +1 more source

Association of high‐dose radioactive iodine therapy with PPM1D‐mutated clonal hematopoiesis in older individuals

open access: yesMolecular Oncology, EarlyView.
In thyroid cancer patients, high‐dose (≥7.4 GBq) radioactive iodine therapy (RAIT) was associated with a higher prevalence of clonal hematopoiesis (variant allele frequency >2%) in individuals aged ≥50 years (OR = 2.44). In silico analyses showed that truncating PPM1D mutations conferred a selective advantage under these conditions.
Jaeryuk Kim   +11 more
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

Home - About - Disclaimer - Privacy