AIMC Topic: Humans

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Are 3D Image Guidance Systems Ready for Use? A Comparative Analysis of 3D Image Guidance Implementations in Minimally Invasive Partial Nephrectomy.

Journal of endourology
Three-dimensional image-guided surgical (3D-IGS) systems for minimally invasive partial nephrectomy (MIPN) can potentially improve the efficiency and accuracy of intraoperative anatomical localization and tumor resection. This review seeks to analyz...

Development of a machine learning model for identifying the optimal situation favoring double-level osteotomy over single-level high tibial osteotomy.

The Knee
BACKGROUND: This study aimed to develop a machine learning (ML) model to identify the optimal situation wherein double-level osteotomy (DLO) is favored for severe varus knees by analyzing unfavorable outcomes. This study hypothesized that there are t...

Severe Hyperkalemia During a Robot-Assisted Total Radical Prostatectomy in a Patient with Stage 3a Chronic Kidney Disease: A Case Report.

A&A practice
A 63-year-old man with stage 3a chronic kidney disease (CKD) and mild hyperkalemia was scheduled for a robot-assisted prostatectomy. He was being treated with lisinopril. Owing to mild hyperkalemia (6.2 mmol/L), lisinopril was discontinued, and sodiu...

Challenges and barriers of using large language models (LLM) such as ChatGPT for diagnostic medicine with a focus on digital pathology - a recent scoping review.

Diagnostic pathology
BACKGROUND: The integration of large language models (LLMs) like ChatGPT in diagnostic medicine, with a focus on digital pathology, has garnered significant attention. However, understanding the challenges and barriers associated with the use of LLMs...

Artificial intelligence-based model for predicting pulmonary arterial hypertension on chest x-ray images.

BMC pulmonary medicine
BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition is often misdiagnosed or a rather long delay occurs from symptom onset to diagnosis, associated with decreased 5-year survival. In this study, we devel...

Automated machine learning for the identification of asymptomatic COVID-19 carriers based on chest CT images.

BMC medical imaging
BACKGROUND: Asymptomatic COVID-19 carriers with normal chest computed tomography (CT) scans have perpetuated the ongoing pandemic of this disease. This retrospective study aimed to use automated machine learning (AutoML) to develop a prediction model...

GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal sinuses.

BMC medical research methodology
INTRODUCTION: The determination of identity factors such as age and sex has gained significance in both criminal and civil cases. Paranasal sinuses like frontal and maxillary sinuses, are resistant to trauma and can aid profiling. We developed a deep...

GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM.

BMC bioinformatics
BACKGROUND: Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the info...

Fully automated kidney image biomarker prediction in ultrasound scans using Fast-Unet+.

Scientific reports
Any kidney dimension and volume variation can be a remarkable indicator of kidney disorders. Precise kidney segmentation in standard planes plays an undeniable role in predicting kidney size and volume. On the other hand, ultrasound is the modality o...