Academic Articles & Research Papers

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...

Domain-Specific Sentiment Analysis: An Optimized Deep Learning Approach for the Financial Markets

Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...

SAM-trace: a fuzzy logic approach in identifying interaction effects in the exacerbation of childhood malnutrition severity

Abstract Pediatric malnutrition remains a major global health challenge. Conventional WHO-based binary classification (Severe Acute Malnutrition (SAM) / Moderate Acute Malnutrition (MAM) relies solely on anthropometric thresholds. It fails ...

Natural language processing

Abstract Approximately 40 years ago, the goal of endowing computers with the capacity to understand natural language began. These efforts were originally callednatural language understanding, which is now more frequently callednatural langu...

Goal setting in stroke rehabilitation: A systematic review and qualitative synthesis of the experiences and perspectives of healthcare professionals.

The Social Impact of Natural Language Processing

Medical sciences have long since established an ethics code for experiments, to minimize the risk of harm to subjects.Natural language processing (NLP) used to involve mostly anonymous corpora, with the goal of enriching linguistic analysis...

An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

Cracking the code: AI’s role in mapping evidence syntheses to the United Nations sustainable development goals

Abstract Background Understanding the alignment and contributions of research to the United Nations Sustainable Development Goals (UN SDGs) is essential for guiding global progress toward these critical targets. Several SDG mapping approach...

Natural Language Processing in Medicine: An Overview

An overview is given of natural language processing applications in medicine. An attempt has been made to enumerate the most important and known international projects and to summarize their goals, principles, methods and results. A section...

HuggingFace's Transformers: State-of-the-art Natural Language Processing

Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to ...

Culling Double Counting in Sequence Images for Fruit Yield Estimation

Exact yield estimation of fruits on plants guaranteed fine and timely decisions on harvesting and marketing practices. Automatic yield estimation based on unmanned agriculture offers a viable solution for large orchards. Recent years have w...

Artificial Intelligence in Routine IVF Practice

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

Mobile system for road sign detection and recognition with template matching

This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illum...

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

Computer Vision for Music Identification

We describe how certain tasks in the audio domain can be effectively addressed using computer vision approaches. This paper focuses on the problem of music identification, where the goal is to reliably identify a song given a few seconds of...

Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Came...

User Interface Aspects of a Human-Hand Simulation System

This paper describes the user interface design for a human-hand simulation system, a virtual environment that produces ground truth data (life-like human hand gestures and animations) and provides visualization support for experiments on co...

A practical introduction to computer vision with OpenCV

Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries Computer Vision is a rapidly expanding area and it is becoming progressively eas...

Computer Vision in Healthcare Applications

The research of computer vision, imaging processing and pattern recognition has made substantial progress during the past several decades.Also, medical imaging has attracted increasing attention in recent years due to its vital component in...

Autonomous Robotic Platform for Precision Viticulture: Integrated Mobility, Multimodal Sensing, and AI-Based Leaf Sampling

Viticulture is facing growing economic and environmental pressures that demand a transition toward intelligent and autonomous crop management systems. Phytopathologies remain one of the most critical threats, causing substantial yield losse...