AIMC Topic: Software

Clear Filters Showing 641 to 650 of 3675 articles

Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis.

BMC musculoskeletal disorders
BACKGROUND: The Kellgren-Lawrence (KL) grading system is the most widely used method to classify the severity of osteoarthritis (OA) of the knee. However, due to ambiguity of terminology, the KL system showed inferior inter- and intra-observer reliab...

Examining how information presentation methods and a chatbot impact the use and effectiveness of electronic health record patient portals: An exploratory study.

Patient education and counseling
OBJECTIVES: Examining information presentation strategies that may facilitate patient education through patient portals is important for effective health education.

Merging Full-Spectrum and Fragment Ion Intensity Predictions from Deep Learning for High-Quality Spectral Libraries.

Journal of proteome research
Spectral libraries are useful resources in proteomic data analysis. Recent advances in deep learning allow tandem mass spectra of peptides to be predicted from their amino acid sequences. This enables predicted spectral libraries to be compiled, and ...

Extension of correlation coefficient based TOPSIS technique for interval-valued Pythagorean fuzzy soft set: A case study in extract, transform, and load techniques.

PloS one
Correlation is an essential statistical concept for analyzing two dissimilar variables' relationships. Although the correlation coefficient is a well-known indicator, it has not been applied to interval-valued Pythagorean fuzzy soft sets (IVPFSS) dat...

GRAND: GAN-based software runtime anomaly detection method using trace information.

Neural networks : the official journal of the International Neural Network Society
Software runtime anomaly detection can detect manifestations (known as anomalies) caused by faults in complex systems before they lead to failure. Whereas most existing methods use external performance indicators, this study uses internal execution t...

Extracting cancer concepts from clinical notes using natural language processing: a systematic review.

BMC bioinformatics
BACKGROUND: Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed...

Creation of Three-dimensional Anatomic Models in Pediatric Surgical Patients Using Cross-sectional Imaging: A Demonstration of Low-cost Methods and Applications.

Journal of pediatric surgery
BACKGROUND: Pediatric surgery patients often present with complex congenital anomalies or other conditions requiring deep understanding of their intricate anatomy. Commercial applications and services exist for the conversion of cross-sectional imagi...

Workflow for Evaluating Normalization Tools for Omics Data Using Supervised and Unsupervised Machine Learning.

Journal of the American Society for Mass Spectrometry
To achieve high quality omics results, systematic variability in mass spectrometry (MS) data must be adequately addressed. Effective data normalization is essential for minimizing this variability. The abundance of approaches and the data-dependent n...

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.

IEEE transactions on neural networks and learning systems
The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Image segmentation, which is crucial for any quantitative analysis, has es...

The preliminary in vitro study and application of deep learning algorithm in cone beam computed tomography image implant recognition.

Scientific reports
To properly repair and maintain implants, which are bone tissue implants that replace natural tooth roots, it is crucial to accurately identify their brand and specification. Deep learning has demonstrated outstanding capabilities in analysis, such a...