Results 131 to 140 of about 166,336 (212)

Infant gut microbiota following cesarean section in the Middle East: a multidisciplinary expert consensus based on a targeted narrative review. [PDF]

Front Pediatr
Aldekhail W, Al-Beltagi M, Indrio F, Al-Nemri AM, Tomerak A, Al Sawai A, Al-Refaee F, Al-Ghanem G, Rozi IH, Alallah J, Khan JM, Abouhazima K, Al-Mannaei K, El-Atawi K, Sleiman R, Miqdady M.   +15 more
europepmc   +1 more source

A global multilingual cocreation of aphasia priority topics through patient and public involvement. [PDF]

Res Involv Engagem
Annoni JM, Charalambous M, Sluga J, Marteel C, Gil J, Strähler R, Eckhardt F, Lyall C, Crovetti D, Mayhew H, Kountouri A, Bennington C, Rubio S.   +12 more
europepmc   +1 more source

The IMPACT framework for evaluating generative AI in critical care: development and multinational consensus validation. [PDF]

Ann Intensive Care
Yeh YC, Shih MC, De Backer D, Celi LA, See KC, Fujii T, Ling L, Mongkolpun W, Hu HW, Chen HY, Chen WC, Cholley B, Fong KK, Ryu HG, Na S, Egi M, Chan WS, Chen KF, Kamaleswaran R, Chuang YC, Yang CJ, Hsiao WL, Lai SR, Ku D, Jahan A, Martin GS, IMPACT Group.   +26 more
europepmc   +1 more source

Voter Engagement in a Family Medicine Residency Clinic. [PDF]

PRiMER
Brown SR, Stauss K, Patel S, Voy C, Dubey S, Langsetmo S, Spielberg F.   +6 more
europepmc   +1 more source

Preoperative Imaging for Cochlear Implantation: A Global Consensus. [PDF]

Otolaryngol Head Neck Surg
Alzhrani F, Alahmadi A, Alshalan A, Abdelsamad Y, Alsanosi A, Acharya A, Kim AH, Macias AR, Gantz B, Buchman C, Jiang D, Cuda D, Jankunaite D, Sprinzl G, Olze H, Anderson I, Shami I, Saunders JE, Gavilan J, Kutz W, Brown KD, Rak K, Telmesani L, Lassaletta L, Bance M, Caversaccio M, Kameswaran M, Zernotti M, Verhaert N, Adunka O, Connolly PF, Van de Heyning P, Caye-Thomasen P, Skarzynski P, Briggs R, Hagen R, Khalil S, Ghossaini SN, Plontke SK, O'Leary SJ, Agrawal SK, Yamasoba T, Lenarz T, Stöver T, Topsakal V, Van Rompaey V, Hagr A.   +46 more
europepmc   +1 more source

Machine Learning for Predicting Coronary Heart Disease Risk in Patients with Hypertension: An Ensemble Modeling Approach. [PDF]

Healthc Inform Res
Hassan FH, Wang S, Miron A.
europepmc   +1 more source

Integrating geospatial intelligence and machine learning for flood susceptibility mapping. [PDF]

Sci Rep
Rahimi M, Malekmohammadi B, Firozjaei MK, Kerachian R, Arsanjani JJ, Tan ML, Awange J, Savic D, Duan Q, AghaKouchak A.   +9 more
europepmc   +1 more source

Biochip-simulated genotype signals enable accurate and interpretable AMR prediction via machine learning. [PDF]

Front Med (Lausanne)
Fu Z.
europepmc   +1 more source

Source camera attribution using a rule-based explainable convolutional neural network. [PDF]

Sci Rep
Nayerifard T, Amintoosi H, Ghaemi Bafghi A.   +2 more
europepmc   +1 more source