Recent advances in applying machine learning and deep learning to detect upper gastrointestinal tract lesions

M Vania, BA Tama, H Maulahela, S Lim - IEEE Access, 2023 - ieeexplore.ieee.org
The clinical application of a real-time artificial intelligence (AI) image processing system to
diagnose upper gastrointestinal (GI) malignancies remains an experimental research and …

[PDF][PDF] Better metrics for evaluating explainable artificial intelligence

A Rosenfeld - Proceedings of the 20th international conference …, 2021 - researchgate.net
This paper presents objective metrics for how explainable artificial intelligence (XAI) can be
quantified. Through an overview of current trends, we show that many explanations are …

Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation

X Liu, P Hu, W Yeung, Z Zhang, V Ho, C Liu… - The Lancet Digital …, 2023 - thelancet.com
Background Comorbidity, frailty, and decreased cognitive function lead to a higher risk of
death in elderly patients (more than 65 years of age) during acute medical events. Early and …

Artificial intelligence in the management of barrett's esophagus and early esophageal adenocarcinoma

FL Dumoulin, FD Rodriguez-Monaco, A Ebigbo… - Cancers, 2022 - mdpi.com
Simple Summary Esophageal adenocarcinoma is increasing in incidence and is the most
common subtype of esophageal cancer in Western societies. AI systems are currently under …

Rapid triage for ischemic stroke: a machine learning-driven approach in the context of predictive, preventive and personalised medicine

Y Zheng, Z Guo, Y Zhang, J Shang, L Yu, P Fu, Y Liu… - EPMA Journal, 2022 - Springer
Background Recognising the early signs of ischemic stroke (IS) in emergency settings has
been challenging. Machine learning (ML), a robust tool for predictive, preventive and …

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

GD Jones, SM Kariuki, AK Ngugi… - The Lancet Digital …, 2023 - thelancet.com
Background Identification of convulsive epilepsy in sub-Saharan Africa relies on access to
resources that are often unavailable. Infrastructure and resource requirements can further …

Integration of infant metabolite, genetic, and islet autoimmunity signatures to predict type 1 diabetes by age 6 years

BJM Webb-Robertson, ES Nakayasu… - The Journal of …, 2022 - academic.oup.com
Context Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically
predisposed children can facilitate interventions to delay or prevent the disease. Objective …

Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic …

HM Rai, J Yoo, A Razaque - Expert Systems with Applications, 2024 - Elsevier
Cancer remains a leading reason of mortality, with the current global death toll estimated at
10 million and projected to surpass 16 million by 2040 as reported by the World Health …

Screening for Barrett's oesophagus: are we ready for it?

A Yusuf, RC Fitzgerald - Current treatment options in gastroenterology, 2021 - Springer
Purpose of review The targeted approach adopted for Barrett's oesophagus (BO) screening
is sub-optimal considering the large proportion of BO cases that are currently missed. We …

[HTML][HTML] Development and validation of a multivariable risk factor questionnaire to detect oesophageal cancer in 2-week wait patients

KMA Ho, A Rosenfeld, Á Hogan, H McBain… - Clinics and Research in …, 2023 - Elsevier
Introduction Oesophageal cancer is associated with poor health outcomes. Upper GI (UGI)
endoscopy is the gold standard for diagnosis but is associated with patient discomfort and …