Results 71 to 80 of about 1,141,315 (287)

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Developing a comprehensive framework for multimodal feature extraction

, 2017
Feature extraction is a critical component of many applied data science workflows. In recent years, rapid advances in artificial intelligence and machine learning have led to an explosion of feature extraction tools and services that allow data ...
de la Vega, Alejandro, McNamara, Quinten, Yarkoni, Tal   +2 more
core   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

A System for Accessible Artificial Intelligence

, 2017
While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them.
D. A. Ferrucci, EM Ronald, F Pedregosa, Ignacio Arnaldo, Jason H. Moore, JH Moore, JH Moore, JH Moore, Karthik Kannappan, Randal S. Olson, RS Olson, Sara Silva, William La Cava, William La Cava   +13 more
core   +1 more source

Applying an Ethical Lens to the Treatment of People With Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The practice of neurology requires an understanding of clinical ethics for decision‐making. In multiple sclerosis (MS) care, there are a wide range of ethical considerations that may arise. These involve shared decision‐making around selection of a disease‐modifying therapy (DMT), risks and benefits of well‐studied medications in comparison to
Methma Udawatta, Farrah J. Mateen
wiley   +1 more source

Artificial intelligence-open science symbiosis in chemoinformatics

Artificial Intelligence in the Life Sciences
In chemoinformatics, artificial intelligence (AI) continues to grow a symbiosis with open science (OS). Such a close AI-OS interaction brings substantial practical benefits in research, scientific dissemination, and education, to name a few areas. The AI-
Filip Miljković, José L. Medina-Franco
doaj   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source

Use of Open-Source Epidemic Intelligence for Infectious Disease Outbreaks, Ukraine, 2022

Emerging Infectious Diseases
Formal infectious disease surveillance in Ukraine has been disrupted by Russia’s 2022 invasion, leading to challenges with tracking and containing epidemics.
Anjali Kannan, Rosalie Chen, Zubair Akhtar, Braidy Sutton, Ashley Quigley, Margaret J. Morris, C. Raina MacIntyre   +6 more
doaj   +1 more source

A GeoSocial Intelligence Framework for Studying & Promoting Resilience to Seasonal Flooding in Jakarta, Indonesia [PDF]

, 2014
PetaJakarta.org is a web-based platform developed to harness the power of social media to gather, sort, and display information about flooding for Jakarta residents in real time.
Holderness, T., Turpin, E., Wickramasuriya, R.   +2 more
core   +1 more source