Academic Articles & Research Papers

Binaural Beat Stimulation Enhances Cognitive Function in Alzheimer’s Disease via Temporal Lobe Activation: An sLORETA Study

Background: The global prevalence of Alzheimer’s disease (AD) has reached 55.2 million. AD is characterized by progressive deterioration in cognition and working memory (WM), which are essential for attention, reasoning, and learning. These...

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...

Application of artificial intelligence in gastroenterology

Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization...

Smart IoT device for in field Black Sigatoka Disease recognition and mapping

Recently banana plantations have been affected by the Black Sigatoka Disease (BSD), producing streaks, lesions and yellow and brown spots on the leaves until the appearance of entire dead parts. The disease causes reductions in yield making...

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...

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

Meta-surface plasmon resonance microscopy for sensitive, high-throughput, and long-term label-free analysis of cell adhesion dynamics

Abstract Quantitative, label-free monitoring of dynamic cell adhesion remains challenging. Meta-Surface Plasmon Resonance Microscopy (Meta-SPRM) is a novel platform integrating bright-field microscopy with engineered Meta-SPR nanocup arrays...

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensu...

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...

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...

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

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...

Artificial Intelligence for Lentigo Maligna: Automated Margin Assessment via Sox-10-Based Melanocyte Density Mapping

Lentigo maligna (LM) is a melanoma in situ with high cumulative sun damage. Histological evaluation of resection margins is difficult and time-consuming. Melanocyte density (MD) is a suitable, quantifiable, and reproducible diagnostic crite...

Two decades of Landsat images reveal spatial and temporal dynamics of invasion and improve species distribution models.

Computer vision and AI-based cell phone usage detection in restricted zones of manufacturing industries

Phone calls are strictly forbidden in certain locations due to the potential security threats. Mobile phones’ growing capabilities have also increased the risk of their misuse in places that are restricted, like manufacturing plants. Unauth...

Generative artificial intelligence

Abstract Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Lever...

Smart_Eye: A Navigation and Obstacle Detection for Visually Impaired People through Smart App

Vision is extremely important in our lives. The loss of sight is a serious issue for anyone. According to the WHO, one-sixth of the world's population suffers from vision impairment. According to World Health Organization (WHO) statistics p...

Identification of Aspergillus at section and species levels by artificial intelligence-based microscopic morphology image recognition

ABSTRACT Rapid and accurate identification of Aspergillus species in clinical microbiology laboratories is crucial for aspergillosis diagnosis and antifungal therapy. However, traditional methods still face challenges in distinguishing phyl...