Results 151 to 160 of about 226,500 (292)

What Is Required for AI to Improve the Assessment and Treatment of Patients With Lower Urinary Tract Dysfunction? ICI‐RS 2025

Neurourology and Urodynamics, EarlyView.
ABSTRACT Introduction Artificial intelligence (AI) is poised to improve the diagnosis and management of lower urinary tract dysfunction (LUTD). Its effective deployment requires prioritization, regulatory oversight, rigorous validation, and clinician and patient engagement.
Glenn T. Werneburg, Michel Wyndaele, John E. Speich, Enrico Finazzi Agro, Mo Belal, Sachin Malde, George Bou Kheir, Emre Huri, Arjun K. Nambiar, Giovanni Mosiello, Riccardo Lombardo, Phil Toozs‐Hobson, Christopher R. Chapple, Alan J. Wein, Paul Abrams, Kevin Rademakers   +15 more
wiley   +1 more source

The Uncharted Territory of the New Obesity Drugs in Users Without Obesity: A Sociomedical Perspective

Obesity, EarlyView.
ABSTRACT The off‐label use of glucagon‐like peptide‐1 receptor agonists (GLP‐1ra) among people without obesity and/or diabetes is rapidly expanding, despite a lack of clinical justification or safety data in this population. This Perspective explores the sociomedical dimensions of this trend, highlighting key research gaps and emerging hypotheses ...
Fernanda Baeza Scagliusi, Bruno Gualano, Pernille Andreassen, Cindi SturtzSreetharan, Sissel Due Jensen, Alexandra Brewis   +5 more
wiley   +1 more source

Community participation in responding to health misinformation. [PDF]

Int J Equity Health
Namata Kamoga RM, Pritam Singh RK, Andrews E, Snow S.   +3 more
europepmc   +1 more source

Bridging the gap between science, policy and stakeholders: Towards sustainable wolf–livestock coexistence in human‐dominated landscapes

People and Nature, EarlyView.
Abstract While the return of wolves (Canis lupus) to many European countries is a conservation milestone, the negative impacts are unevenly distributed across society, placing high pressure on livestock grazing systems. For this perspective, scientists from diverse disciplines and geographical backgrounds reflect on the state of livestock–wolf ...
Emu‐Felicitas Ostermann‐Miyashita, Hannah Kirkland, Ann Eklund, Darragh Hare, Hugh A. H. Jansman, Christian Kiffner, John D. C. Linnell, Robin Rigg, Suzanne A. Stone, Sandra Uthes, Manuela von Arx, Hannes J. König   +11 more
wiley   +1 more source

Analyzing Misinformation and Disinformation: Understanding Swiss COVID-19 Narratives Through Natural Language Processing Analysis. [PDF]

JMIR Infodemiology
Germani F, Spitale G, Fritschi F, Merten S, Biller-Andorno N.   +4 more
europepmc   +1 more source

The impact of COVID‐19 on public perceptions of wild meat in Central Africa

People and Nature, EarlyView.
Abstract Wild meat is a significant source of food and income generation in Central Africa. However, there is little knowledge of how the assumed link between COVID‐19 and wild meat consumption has been discussed by the media and received by the public. In this study, we conducted media content analysis of 264 articles published in 2019–2020 related to
Yuhan Li, Lude Kinzonzi, Paul Loundou, Divin Malekani, Krossy Mavakala, Christian Mikolo Yobo, Katharine Abernethy, Matilda Eve Dunn, Donald Midoko Iponga, Robert Mwinyihali, Joss Wright, Eleanor Jane Milner‐Gulland, Lauren Coad, Juliet H. Wright, Daniel W. S. Challender   +14 more
wiley   +1 more source

Development and validation of a tool for detecting misinformation risk in diet, nutrition, and health content (Diet-MisRAT). [PDF]

Sci Rep
Ruani A, Reiss MJ, Kalea AZ.
europepmc   +1 more source

Training Dental Researchers in Digital Outreach: A Course Model for Science Communication and Public Engagement

Journal of Dental Education, EarlyView.
Vandilson Rodrigues
wiley   +1 more source

Deep learning‐based ecological analysis of camera trap images is impacted by training data quality and quantity

Remote Sensing in Ecology and Conservation, EarlyView.
Machine learning image classifiers are increasingly being used to automate camera trap image labelling, but we don't know how much ML model accuracy matters for downstream ecological analyses. Using two large data sets from an African savannah and an Asian dry forest ecosystem, we compared human labelled data with predictions from deep‐learning models ...
Peggy A. Bevan, Omiros Pantazis, Holly A.I. Pringle, Guilherme Braga Ferreira, Daniel J. Ingram, Emily K. Madsen, Liam Thomas, Dol Raj Thanet, Thakur Silwal, Santosh Rayamajhi, Gabriel J. Brostow, Oisin Mac Aodha, Kate E. Jones   +12 more
wiley   +1 more source

Misinformation and Profitability of Hepatitis B Virus Claims on Instagram: Formative Cross-Sectional Study. [PDF]

JMIR Form Res
Warner ZC, Turner CA, Alvarez R, Gallegos-Orozco JF, Green A, Warner EL.   +5 more
europepmc   +1 more source