Academic Articles & Research Papers

Bayesian methods in health technology assessment: a review.

BACKGROUND: Bayesian methods may be defined as the explicit quantitative use of external evidence in the design, monitoring, analysis, interpretation and reporting of a health technology assessment. In outline, the methods involve formal co...

Artificial neural network–based model for sleep quality prediction for frontline medical staff during major medical assistance

Background: The sleep quality of medical staff was severely affected during COVID-19, but the factors influencing the sleep quality of frontline staff involved in medical assistance remained unclear, and screening tools for their sleep qual...

A pairwise residue contact area-based mean force potential for discrimination of native protein structure

Abstract Background Considering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popula...

Deep learning-based multimodal data fusion in bone tumor management: Advances in clinical decision support

Bone tumors (BTs)—including osteosarcoma, Ewing sarcoma, and chondrosarcoma—are rare but biologically complex malignancies characterized by pronounced heterogeneity in anatomical location, histological subtype, and molecular alterations. Re...

Statistical data for the tensile properties and static fatigue of sic-based bundles

Due to their high specific strength at elevated temperatures and resistance to oxidative environments, SiC-based fibers are of great interest for the reinforcement of ceramic matrix composites. They are however subjected to a slow crack gro...

Automated measurement of CD8+ T-cell distribution at the tumor epithelial–stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based on PD-L1 expression have limited predictive power for these therapies, motivating developm...

Digital quality gradient and the burden of elderly depression: A spatial multi kernel SVR analysis of socio economically vulnerable groups in England

Digital infrastructure is increasingly understood as part of the contemporary built environment and as a policy-relevant area-level correlate of older adults’ mental health. Existing studies have often relied on linear models and have paid ...

Artificial intelligence-driven anthropometric assessment for young children: evaluating the accuracy and practicality of a digital image-based length and weight prediction tool

Background Monitoring early childhood growth is vital, as growth faltering could indicate nutritional or health issues requiring prompt intervention. Our study’s aim was to assess the performance of a length-weight artificial intelligence (...

Deep learning prediction of pathological complete response in breast cancer using Mamba architecture

Abstract Deep learning is capable of efficiently predicting the therapeutic efficacy of neoadjuvant chemotherapy (NAC) in breast cancer. However, current methods predominantly rely on convolutional neural networks or transformer architectur...

Development and validation of an interpretable machine learning model for predicting the risk of coronary heart disease risk in diabetes mellitus patients: a dual-center retrospective study

Abstract Background Diabetes mellitus (DM) combined with coronary heart disease (CHD) significantly increases the risk of cardiovascular events with a greater mortality rate. Therefore, establishing a predictive model can help DM patients r...

Exploring feature selection and classification methods for predicting heart disease

Machine learning has been used successfully to improve the accuracy of computer-aided diagnosis systems. This paper experimentally assesses the performance of models derived by machine learning techniques by using relevant features chosen b...

Argumentation approaches for explanaible AI in medical informatics

Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are often considered black boxes as they do not provide any explanation about how outputs are derived from inputs or why a decision is taken. There...

The Renewed Promise of Medical Informatics

The promise of the field of Medical Informatics has been great and its impact has been significant. In 1999, the Yearbook editors of the International Medical Informatics Association (IMIA) - also the authors of the present paper - sought t...

Correction: Five-year dementia prediction and decision support system based on real-world data

LocateP: Genome-scale subcellular-location predictor for bacterial proteins

Abstract Background In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, ...

The Cornerstones of Medical Informatics

The changes in the health care system over the next decade are goint to make the last 20 years seem like good old days of relative stability. We will continue to see new drugs, new devices, and new techniques; however, the true megachanges ...

Prediction of the Leaf Primordia of Potato Tubers Using Sensor Fusion and Wavelength Selection

The sprouting of potato tubers during storage is a significant problem that suppresses obtaining high quality seeds or fried products. In this study, the potential of fusing data obtained from visible (VIS)/near-infrared (NIR) spectroscopic...

ODE, regression, and ANN models for energy forecasting: Egypt as a study case

Energy plays a crucial role in national development, influencing critical sectors such as industry, agriculture, healthcare, and education. Accurate energy consumption prediction is essential for efficient energy management, helping prevent...

Soil Geochemical Properties Influencing the Diversity of Bacteria and Archaea in Soils of the Kitezh Lake Area, Antarctica

It is believed that polar regions are influenced by global warming more significantly, and because polar regions are less affected by human activities, they have certain reference values for future predictions. This study aimed to investiga...

Emerging mutations in envelope protein of SARS-CoV-2 and their effect on thermodynamic properties

Structural proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are potential drug targets due to their role in the virus life cycle. The envelope (E) protein is one of the structural proteins; plays a critical role in v...