Results 131 to 140 of about 52,163 (250)

Evaluation Framework for Bruise Detection: Systematic ALS/White-Light Training and Skin-Tone Balancing with Deep Learning. [PDF]

Sensors (Basel)
Aminfar K, Scafide K, Wojtusiak J, Lattanzi D.   +3 more
europepmc   +1 more source

A Review of Artificial Intelligence in Ophthalmology: Key Aspects, Challenges, and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is increasingly reshaping ophthalmology because the specialty depends heavily on structured imaging, quantitative measurements, and repeatable diagnostic workflows. This review provides a clinically grounded and translationally oriented synthesis of AI in ophthalmology, covering methodological foundations ...
Partha Pratim Ray
wiley   +1 more source

Automated bone marrow cell classification using ensemble learning: performance, generalization, and clinical interpretability. [PDF]

Front Med (Lausanne)
Mehmood S, Zubair M, Abbas S, Alharbi RM, Alduailij M, Khan MA, Ghazal TM.   +6 more
europepmc   +1 more source

Facilitating the timely diagnosis of Lennox–Gastaut syndrome: A checklist to support clinical practice

Epileptic Disorders, EarlyView.
Abstract Objective To develop and evaluate a simple‐to‐use checklist to support physicians with the timely diagnosis of Lennox–Gastaut syndrome (LGS). Methods A panel of 10 pediatric and adult epileptologists used the International League Against Epilepsy (ILAE) criteria for LGS classification and definition to develop seven questions for the checklist,
Nicola Specchio, Alexis Arzimanoglou, Stéphane Auvin, Antonio Gil‐Nagel, Lieven Lagae, Rima Nabbout, Susanne Schubert‐Bast, Adam Strzelczyk, Eugen Trinka, J. Helen Cross   +9 more
wiley   +1 more source

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale. [PDF]

JAMIA Open
Mohapatra A, Porth R, Wong S, Hardway H, Piatkowski G, Shang J, Amat MJ, Flier S, Salsman A, Fitzgerald T, Shammout A, Rubins D, Miller A, Jegadeesan V, Ravi A, Feuerstein JD.   +15 more
europepmc   +1 more source

Approximating Perfect Recall When Model Checking Strategic Abilities.

We investigate the notion of bounded recall in the context of model checking ATL ∗ and ATL specifications in multi- agent systems with imperfect information. We present a novel three-valued semantics for ATL ∗ , respectively ATL , under bounded recall and imperfect information, and study the cor- responding model checking problems. Most importantly, we
Francesco Belardinelli, Alessio Lomuscio, Vadim Malvone   +2 more
openaire   +2 more sources

Use of artificial intelligence in magnetic resonance imaging across the epileptic patient's journey: A meta‐analysis of four clinical applications

Epilepsia, EarlyView.
Abstract Objective The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support clinical decision‐making in epilepsy. However, there currently lacks an appropriate assessment of clinical utility and study rigor of current AI/ML‐driven models that are targeted toward supporting ...
Judy Chen, Ella Sahlas, Yigu Zhou, Natalie Chen, Jim Xie, Farhan Wadia, Lorenzo Caciagli, Aristides Hadjinicolaou, Alexander G. Weil, Roy W. Dudley, Dewi V. Schrader, Andrea Bernasconi, Neda Bernasconi, Boris C. Bernhardt   +13 more
wiley   +1 more source

Explainable deep learning-based comparative study for guava fruit and leaf disease classification: advancing agricultural diagnostics through AI. [PDF]

Front Plant Sci
Zhou Z.
europepmc   +1 more source

Epileptogenic lesions in the Australian epilepsy project: A harmonized 3‐T magnetic resonance imaging protocol and its diagnostic yield

Epilepsia, EarlyView.
Abstract Objective Detection of epilepsy‐causing structural brain lesions on magnetic resonance imaging (MRI) is critical for diagnosis, prognosis, and treatment planning in people with epilepsy. We aimed to establish an epilepsy‐directed multisite harmonized 3‐T MRI acquisition protocol for the Australian Epilepsy Project (AEP) and describe the ...
David N. Vaughan, David F. Abbott, Amanda Anderson, Greg Fitt, Suyi Ooi, Heath Pardoe, Donna Parker, Yuliya Perchyonok, Eric Pierre, Chris Kokkinos, Robert E. Smith, Michael Stewart, Bahman Tahayori, Chris Tailby, Graeme D. Jackson, the Australian Epilepsy Project Investigators, Zanfina Ademi, Patrick Kwan, Karen Oliver, Mangor Pedersen   +19 more
wiley   +1 more source

Explainable AI for mortality prediction: a comparative study using the MIMIC-III dataset. [PDF]

BMJ Health Care Inform
Shafiabady N, Akume D, Haghighat M, Ud Din F, Sattarshetty K, Karim A, Zhou J, Alsharaydeh E.   +7 more
europepmc   +1 more source