Results 151 to 160 of about 1,911,499 (379)
Dual targeting of AKT and mTOR using MK2206 and RAD001 reduces tumor burden in an intracardiac colon cancer circulating tumor cell xenotransplantation model. Analysis of AKT isoform‐specific knockdowns in CTC‐MCC‐41 reveals differentially regulated proteins and phospho‐proteins by liquid chromatography coupled mass spectrometry. Circulating tumor cells
Daniel J. Smit+19 more
wiley +1 more source
Medical errors and communication
Carlos M. San Román-Terán+1 more
doaj +1 more source
The pattern of non-intercepted medication errors in a university affiliated teaching hospital [PDF]
INTRODUCTION: The primary goal of reducing medication errors is to eliminate errors that reach the patient. We aimed to study the pattern of interception of medication errors along the medication use process.
Cheung, BMY+3 more
core
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain+3 more
wiley +1 more source
Performant ASR Models for Medical Entities in Accented Speech [PDF]
Recent strides in automatic speech recognition (ASR) have accelerated their application in the medical domain where their performance on accented medical named entities (NE) such as drug names, diagnoses, and lab results, is largely unknown. We rigorously evaluate multiple ASR models on a clinical English dataset of 93 African accents.
arxiv
Inhibitor of DNA binding‐1 is a key regulator of cancer cell vasculogenic mimicry
Elevated expression of transcriptional regulator inhibitor of DNA binding 1 (ID1) promoted cancer cell‐mediated vasculogenic mimicry (VM) through regulation of pro‐angiogenic and pro‐cancerous genes (e.g. VE‐cadherin (CDH5), TIE2, MMP9, DKK1). Higher ID1 expression also increased metastases to the lung and the liver.
Emma J. Thompson+11 more
wiley +1 more source
MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes [PDF]
Several studies showed that Large Language Models (LLMs) can answer medical questions correctly, even outperforming the average human score in some medical exams. However, to our knowledge, no study has been conducted to assess the ability of language models to validate existing or generated medical text for correctness and consistency.
arxiv
Alectinib resistance in ALK+ NSCLC depends on treatment sequence and EML4‐ALK variants. Variant 1 exhibited off‐target resistance after first‐line treatment, while variant 3 and later lines favored on‐target mutations. Early resistance involved off‐target alterations, like MET and NF2, while on‐target mutations emerged with prolonged therapy.
Jie Hu+11 more
wiley +1 more source
B‐cell chronic lymphocytic leukemia (B‐CLL) and monoclonal B‐cell lymphocytosis (MBL) show altered proteomes and phosphoproteomes, analyzed using mass spectrometry, protein microarrays, and western blotting. Identifying 2970 proteins and 316 phosphoproteins, including 55 novel phosphopeptides, we reveal BCR and NF‐kβ/STAT3 signaling in disease ...
Paula Díez+17 more
wiley +1 more source
The Multicultural Medical Assistant: Can LLMs Improve Medical ASR Errors Across Borders? [PDF]
The global adoption of Large Language Models (LLMs) in healthcare shows promise to enhance clinical workflows and improve patient outcomes. However, Automatic Speech Recognition (ASR) errors in critical medical terms remain a significant challenge. These errors can compromise patient care and safety if not detected.
arxiv