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Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis.

International journal of biological macromolecules
In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using integrated bioinformatic and machine learning analysis. The results showed that a total of 88 functi...

Using machine learning approaches to develop a fast and easy-to-perform diagnostic tool for patients with light chain amyloidosis: a retrospective real-world study.

Annals of hematology
Immunoglobulin light chain (AL) amyloidosis is a severe disorder caused by the accumulation of amyloid fibrils, leading to organ failure. Early diagnosis is crucial to prevent irreversible damage, yet it remains a challenge due to nonspecific symptom...

Deep Learning Approaches for the Assessment of Germinal Matrix Hemorrhage Using Neonatal Head Ultrasound.

Sensors (Basel, Switzerland)
Germinal matrix hemorrhage (GMH) is a critical condition affecting premature infants, commonly diagnosed through cranial ultrasound imaging. This study presents an advanced deep learning approach for automated GMH grading using the YOLOv8 model. By a...

Identification of metabolism related biomarkers in obesity based on adipose bioinformatics and machine learning.

Journal of translational medicine
BACKGROUND: Obesity has emerged as a growing global public health concern over recent decades. Obesity prevalence exhibits substantial global variation, ranging from less than 5% in regions like China, Japan, and Africa to rates exceeding 75% in urba...

Prediction of femoral head collapse in osteonecrosis using deep learning segmentation and radiomics texture analysis of MRI.

BMC medical informatics and decision making
BACKGROUND: Femoral head collapse is a critical pathological change and is regarded as turning point in disease progression in osteonecrosis of the femoral head (ONFH). In this study, we aim to build an automatic femoral head collapse prediction pipe...

Pharmacy students' perception and knowledge of chat-based artificial intelligence tools at a Nigerian University.

BMC medical education
BACKGROUND: Chat-based Artificial Intelligence (AI) tools, such as ChatGPT, are becoming integral to various aspects of pharmacy education. However, their integration into the curriculum faces challenges due to students' varying levels of knowledge a...

Medical students and house officers' perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is one of the sectors of medical research that is expanding the fastest right now in healthcare. AI has rapidly advanced in the field of medicine, helping to treat a variety of illnesses and reducing the numbe...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BMC gastroenterology
BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-...

Innovative label-free lymphoma diagnosis using infrared spectroscopy and machine learning on tissue sections.

Communications biology
The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinical manifestations. There is a need for inexpensive tools that require minimal expertise and are accessible for routine laboratories. Contrastingly, cu...

Validation of artificial intelligence-based application to estimate nutrients in daily meals.

Journal of cardiology
BACKGROUND: Diet modification is a mainstay for the successful management of metabolic syndrome and potentially may reduce the risk of cardiovascular disease. Accurate estimation of essential nutrients in daily meals is currently challenging to quant...