Academic Articles & Research Papers

Artificial intelligence tools in dermatology education: A scoping review on their application, efficacy, and limitations

Introduction: Artificial Intelligence (AI) is increasingly explored for medical education, and dermatology, with its visual diagnostic focus, holds promise for AI-enhanced learning. However, evidence on its educational effectiveness remains...

What radiologists need to know about patients’ expectations: P.A.T.I.E.N.T.S C.A.R.E.R.S A.I.M.S

Abstract The Patient Advisory Group (PAG) of the European Society of Radiology aims to highlight, in this short paper, patients’ expectations from the radiological community and support workers, throughout the patient’s medical imaging jour...

Cervical Cancer Diagnosis Based on Multi-Domain Features Using Deep Learning Enhanced by Handcrafted Descriptors

Cervical cancer, among the most frequent adverse cancers in women, could be avoided through routine checks. The Pap smear check is a widespread screening methodology for the timely identification of cervical cancer, but it is susceptible to...

Applications of Artificial Intelligence in Dentomaxillofacial Diagnostics

Introduction: The introduction of artificial intelligence-driven applications is revolutionizing dentomaxillofacial imaging. Objectives: To describe the current status of artificial intelligence applications in dentomaxillofacial diagnosti...

Low-Field MRI Reduces Cost and Environmental Impact While Maintaining Diagnostic Performance in Resource-Limited Settings: A Narrative Review With Cardiovascular Focus.

Platform-agnostic quantification for molecular interception of oral and esophageal malignancies: a global study addressing the diagnostic divide.

An automated deep learning framework for brain tumor classification using MRI imagery

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

Application of artificial intelligence to the electrocardiogram

Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG,...

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein

Fibroblast activation protein (FAP) is a highly specific biomarker overexpressed in cancer-associated fibroblasts, making it a promising diagnostic target. Developing novel high-affinity molecular probes for FAP-targeted diagnostics remains...

AI enhanced diagnostic accuracy and workload reduction in hepatocellular carcinoma screening

Abstract Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies us...

Large language model bias auditing for periodontal diagnosis using an ambiguity-probe methodology: a pilot study

BackgroundLarge Language Models (LLMs) in healthcare holds immense promise yet carries the risk of perpetuating social biases. While artificial intelligence (AI) fairness is a growing concern, a gap exists in understanding how these models ...

Machine minds: Artificial intelligence in psychiatry

Diagnostic and interventional aspects of psychiatric care can be augmented by the use of digital health technologies. Recent studies have tried to explore the use of artificial intelligence-driven technologies in screening, diagnosing, and ...

Artificial Intelligence-Driven Salivary Biomarkers for Detection and Risk Stratification of Oral Potentially Malignant Disorders and OSCC: A Protocol for a Systematic Review

Objective This systematic review protocol aims to synthesize evidence on artificial intelligence-driven analysis of salivary biomarkers for the detection, risk stratification and differentiation of OPMDs and OSCC, with particular attention ...

AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction

This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...

Neural Networks and Artificial’s Intelligence’s Algorithms in the Tasks of Diagnostics Foreign Bodies

The paper considers a device in which information about the presence of a foreign body a fragment in a wound is obtained using a special compact sensor: a mechanical elastic flexible rod, which is placed in a protective soft tube and connec...

Artificial intelligence in diagnostic pathology

Digital pathology (DP) is being increasingly employed in cancer diagnostics, providing additional tools for faster, higher-quality, accurate diagnosis. The practice of diagnostic pathology has gone through a staggering transformation wherei...

Accuracy and reliability of Manus, ChatGPT, and Claude in case-based dental diagnosis

IntroductionArtificial intelligence (AI), particularly large language models (LLMs), is transforming healthcare education and clinical decision-making. While models like ChatGPT and Claude have demonstrated utility in medical contexts, thei...

Imago Imaginis

Teaching formal analysis in art history often reveals gaps between students’ visual perception and their analytical articulation. This study explores the pedagogical potential of AI image generators in art history education, focusing on the...