AIMC Topic: Databases, Factual

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Sentiment classification for telugu using transformed based approaches on a multi-domain dataset.

Scientific reports
Sentiment analysis is an essential component of Natural Language Processing (NLP) in resource-abundant languages such as English. Nevertheless, poor-resource languages such as Telugu have experienced limited efforts owing to multiple considerations, ...

Fully automated measurement of paediatric cerebral palsy pelvic radiographs with BoneFinder : external validation using a national surveillance database.

The bone & joint journal
AIMS: BoneFinder is a machine-learning tool that can automatically calculate Reimers migration percentage (RMP) and head-shaft angle (HSA) from paediatric cerebral palsy (CP) pelvic radiographs. This study's primary aim was to compare BoneFinder's fu...

Evaluation of meibomian gland dysfunction with deep learning model considering different datasets and gland morphology.

Computers in biology and medicine
Meibomian gland dysfunction (MGD) is recognized as the primary cause of evaporative-type dry eye disease (DED). Diagnosis typically involves assessing meibomian gland (MG) morphology alongside symptom evaluation. Traditionally, experts manually grade...

Radio DINO: A foundation model for advanced radiomics and AI-driven medical imaging analysis.

Computers in biology and medicine
Radiomics is transforming medical imaging by extracting complex features that enhance disease diagnosis, prognosis, and treatment evaluation. However, traditional approaches face significant challenges, such as the need for manual feature engineering...

Data-driven trends in critical care informatics: a bibliometric analysis of global collaborations using the MIMIC database (2004-2024).

Computers in biology and medicine
BACKGROUND: The Medical Information Mart for Intensive Care (MIMIC) database has become a cornerstone resource for critical care research, enabling advances in outcome prediction, machine learning, and patient management. However, comprehensive bibli...

SER inspired deep learning approach to detect cardiac arrhythmias in electrocardiogram signals using Temporal Convolutional Network and graph neural network.

Computers in biology and medicine
Electrocardiogram (ECG) signals play a critical role in diagnosing cardiovascular diseases (CVDs), yet automated ECG classification remains challenging due to inter-patient variability, signal noise, and heart rhythm complexity. To address these chal...

Blockchain-aided comparative study of heart disease detection using machine learning-based approaches with an expanded dataset.

Computers in biology and medicine
Heart disease, also known as cardiovascular disease (CVD), is a diverse set of conditions that disrupt the normal functioning of the cardiovascular system by narrowing the coronary arteries. These arteries are used for blood circulation and the deliv...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...

Advancing AI-driven surveillance systems in hospital: A fine-grained instance segmentation dataset for accurate in-bed patient monitoring.

Computers in biology and medicine
In the era of digital health, artificial intelligence (AI)-driven patient monitoring systems have attracted growing interest for their potential to prevent accidents in clinical settings. However, the advancement of these systems requires the availab...

Detection of breast cancer using fractional discrete sinc transform based on empirical Fourier decomposition.

Bio-medical materials and engineering
Breast cancer is the most common cause of death among women worldwide. Early detection of breast cancer is important; for saving patients' lives. Ultrasound and mammography are the most common noninvasive methods for detecting breast cancer. Computer...