Results 141 to 150 of about 7,486,367 (380)

A Graph Framework for Multimodal Medical Information Processing [PDF]

arXiv, 2016
Multimodal medical information processing is currently the epicenter of intense interdisciplinary research, as proper data fusion may lead to more accurate diagnoses. Moreover, multimodality may disambiguate cases of co-morbidity. This paper presents a framework for retrieving, analyzing, and storing medical information as a multilayer graph, an ...
arxiv  

Medical error: the second victim [PDF]

, 2000
Albert W. Wu
openalex   +1 more source

Inhibitor of DNA binding‐1 is a key regulator of cancer cell vasculogenic mimicry

Molecular Oncology, EarlyView.
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, Emma L. Dorward, Kristyn Jurrius, Nathalie Nataren, Markus Tondl, Kay K. Myo Min, Michaelia P. Cockshell, Anahita Fouladzadeh, John Toubia, Mark DeNichilo, Delphine Merino, Claudine S. Bonder   +11 more
wiley   +1 more source

MET and NF2 alterations confer primary and early resistance to first‐line alectinib treatment in ALK‐positive non‐small‐cell lung cancer

Molecular Oncology, EarlyView.
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, Ning Ding, Xiaobo Xu, Yedan Chen, Yong Zhang, Jingwen Liu, Jiebai Zhou, Hairong Bao, Donghui Zhang, Yijun Song, Yang Shao, Yuanlin Song   +11 more
wiley   +1 more source

Accreditation's role in reducing medical errors [PDF]

, 2000
Dennis S. O’Leary
openalex   +1 more source

Tonic signaling of the B‐cell antigen‐specific receptor is a common functional hallmark in chronic lymphocytic leukemia cell phosphoproteomes at early disease stages

Molecular Oncology, EarlyView.
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, Pablo Juanes‐Velasco, Marina L. García‐Vaquero, Conrad Droste, Alicia Landeira‐Viñuela, Miguel Alcoceba, Helena Fidalgo‐Gómez, Sara Misiego‐Herrero, Almudena Navarro‐Bailón, Mónica Baile, José M. Bastida, Jose Manuel Sanchez‐Santos, Rafael Góngora, Julia Almeida, Marcos Gonzalez‐Diaz, Alberto Orfao, Javier De Las Rivas, Manuel Fuentes   +17 more
wiley   +1 more source

Medical errors and communication

Spanish Journal of Medicine, 2022
Carlos M. San Román-Terán, Ricardo Gómez-Huelgas   +1 more
doaj   +1 more source

Performant ASR Models for Medical Entities in Accented Speech [PDF]

arXiv
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  

Aberrant expression of nuclear prothymosin α contributes to epithelial‐mesenchymal transition in lung cancer

Molecular Oncology, EarlyView.
Nuclear prothymosin α inhibits epithelial‐mesenchymal transition (EMT) in lung cancer by increasing Smad7 acetylation and competing with Smad2 for binding to SNAI1, TWIST1, and ZEB1 promoters. In early‐stage cancer, ProT suppresses TGF‐β‐induced EMT, while its loss in the nucleus in late‐stage cancer leads to enhanced EMT and poor prognosis.
Liyun Chen, Chung‐Teng Wang, Jia‐Ming Chang, Ai‐Li Shiau, Gia‐Shing Shieh, Yau‐Lin Tseng, Yi‐Ting Yen, Tang‐Hsiu Huang, Li‐Hsin Cheng, Yu‐Chih Wu, Chao‐Liang Wu, Bing‐Hua Su, Pensee Wu   +12 more
wiley   +1 more source

MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes [PDF]

arXiv
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