Academic Articles & Research Papers

Ultrasound-Based Radiomics and Deep Learning for Prediction of Lateral and Central Lymph Node Metastasis and BRAF Gene Mutation in Papillary Thyroid Carcinoma.

Privacy and Artificial Intelligence

Artificial intelligence is a rapidly developing field of research with many practical applications. Congruent to advances in technologies that enable big data, deep learning, and neural networks to train, learn, and predict, artificial inte...

A Generative Super‐Resolution Model for Enhancing Tropical Cyclone Wind Field Intensity and Resolution

Abstract Extreme winds associated with tropical cyclones (TCs) can cause significant loss of life and economic damage globally, highlighting the need for accurate, high‐resolution modeling and forecasting for wind. However, due to their coa...

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and...

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...

DCN-Deeplabv3+: A Novel Road Segmentation Algorithm Based on Improved Deeplabv3+

Road segmentation is an important task in the field of semantic segmentation, and the Deeplabv3+ algorithm, which is commonly used for road segmentation, has shortcomings, such as numerous parameters and a tendency to lose detailed informat...

Artificial Intelligence for Intraoperative Guidance

OBJECTIVE: The aim of this study was to develop and evaluate the performance of artificial intelligence (AI) models that can identify safe and dangerous zones of dissection, and anatomical landmarks during laparoscopic cholecystectomy (LC)....

Big Data for Energy Management and Energy-Efficient Buildings

European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim o...

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...

A review of prediction methods for moving target trajectories

With the rapid emergence of mobile terminal equipment in intelligent transportation system, the deep understanding and accurate prediction of moving target trajectories are capable of reducing the traffic accident probability, and promoting...

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...

Tangermeme: a toolkit for understanding cis-regulatory logic using deep learning models.

A review of optimization strategies for deep and machine learning in diabetic macular edema

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

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...

MassNet: billion-scale AI-ready mass spectral corpus empowering scalable deep learning in proteomics.

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...

Artificial Intelligence in Pathology

As in other domains, artificial intelligence is becoming increasingly important in medicine. In particular,deep learning-based pattern recognition methods can advance the field of pathology byincorporating clinical, radiologic, and genomic ...

Artificial Intelligence and Deep Learning in Ophthalmology

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to i...

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...