Diagnosis and Treatment Protocol for COVID-19 Patients (Tentative 9th Version)
Infectious Diseases & Immunity, 2022 The General Office of National Health Commission & the General Office of National Administration of Traditional Chinese Medicine +1 more
doaj +1 more source
Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact [PDF]
arXiv, 2020 This paper provides an overview of the current and near-future applications of Artificial Intelligence (AI) in Medicine and Health Care and presents a classification according to their ethical and societal aspects, potential benefits and pitfalls, and issues that can be considered controversial and are not deeply discussed in the literature.
arxiv
Interprofessional communication with hospitalist and consultant physicians in general internal medicine : a qualitative study [PDF]
, 2012 This study helps to improve our understanding of the collaborative environment in GIM, comparing the communication styles and strategies of hospitalist and consultant physicians, as well as the experiences of providers working with them. The implications
A Atwal +54 more
core +2 more sources
Molecular Oncology, EarlyView.Tumor microenvironment drives cancer formation and progression. We analyzed the role of human cancer‐associated adipocytes from patients with renal cell carcinoma (RCC) stratified as lean, overweight, or obese. RNA‐seq demonstrated that, among the most altered genes involved in the tumor–stroma crosstalk, are ADAM12 and CYP1B1, which were proven to be ...
Sepehr Torabinejad +13 more
wiley +1 more source
Primary extranodal diffuse large B‐cell lymphoma: Molecular features, treatment, and prognosis
Aging and Cancer, Volume 3, Issue 3-4, Page 133-146, September-December 2022., 2022 One‐third of DLBCL arises from extranodal organs and is challenging to manage. Molecular features are critical to elucidate the differences in clinical features, predict the disease prognosis, and improve effective targeted therapeutic strategies. Abstract Diffuse large B‐cell lymphoma (DLBCL) is the most common subtype of non‐Hodgkin's lymphoma and ...
Si‐Yuan Chen +3 more
wiley +1 more source
Work-based assessment within Malta’s specialist training programme in family medicine [PDF]
, 2014 The Specialist Training Programme in Family Medicine (STPFM) – Malta was drawn up by the Malta College of Family Doctors in 2006, approved by Malta’s Specialist Accreditation Committee, and launched in 2007 by the Primary Health Care Department and ...
Abela, Gunther, Sammut, Mario R.
core
La rappresentazione del rapporto tra utenti e sistema sanitario: I modelli culturali dei medici di medicina generale - The representation of the relationship between users and healthcare system: Cultural models of general practitioners [PDF]
, 2016 The present research study explores the emotional and symbolic representation of the Italian healthcare system and specifically of general medical services reported by a group of Italian general practitioners.
Caputo, A. +5 more
core +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Factors modulating 99mTc‐MAA planar lung dosimetry for 90Y radioembolization
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose To investigate the accuracy and biases of predicted lung shunt fraction (LSF) and lung dose (LD) calculations via 99mTc‐macro‐aggregated albumin (99mTc‐MAA) planar imaging for treatment planning of 90Y‐microsphere radioembolization.
Benjamin P. Lopez +4 more
wiley +1 more source
Machine Learning Model Interpretability for Precision Medicine [PDF]
arXiv, 2016 Interpretability of machine learning models is critical for data-driven precision medicine efforts. However, highly predictive models are generally complex and are difficult to interpret. Here using Model-Agnostic Explanations algorithm, we show that complex models such as random forest can be made interpretable. Using MIMIC-II dataset, we successfully
arxiv