AIMC Topic: Male

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Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.

Scientific reports
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, wh...

Unsupervised self-organising map classification of Raman spectra from prostate cell lines uncovers substratified prostate cancer disease states.

Scientific reports
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics ...

Prediction of pulmonary embolism by an explainable machine learning approach in the real world.

Scientific reports
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this...

What is the influence of psychosocial factors on artificial intelligence appropriation in college students?

BMC psychology
BACKGROUND: In recent years, the adoption of artificial intelligence (AI) has become increasingly relevant in various sectors, including higher education. This study investigates the psychosocial factors influencing AI adoption among Peruvian univers...

Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan.

BMC public health
Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, and its incidence and prevalence are increasing in many countries. Modeling of CVD plays a crucial role in understanding the trend of CVD death cases, evaluating the e...

Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.

Langenbeck's archives of surgery
BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the...

Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.

Lung cancer (Amsterdam, Netherlands)
BACKGROUND: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with ad...

Identification of optimal portal pressure decrease to control ascites while minimizing HE after TIPS: A multicenter study.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Clinically significant portal hypertension in patients with liver cirrhosis can lead to refractory ascites. A TIPS treats clinically significant portal hypertension but may cause overt hepatic encephalopathy (oHE). Our aim was to...

Exploring the potential of machine learning models to predict nasal measurements through facial landmarks.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Information on predicting the measurements of the nose from selected facial landmarks to assist in maxillofacial prosthodontics is lacking.