AIMC Topic: Machine Learning

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Evaluation of inflammatory markers in survival analysis of patients undergoing radical cystectomy using machine learning.

World journal of urology
BACKGROUND: We aimed to create a Machine learning (ML) model using patient demographic, clinical and pathological data for prediction of overall survival in patients treated with radical cystectomy (RC). Secondly, we evaluated whether inflammatory ma...

Prognostic value of admission ROTEM in trauma: enhancing 30-day all-cause mortality prediction using machine learning.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Haemorrhage is a leading cause of trauma death, yet early coagulation markers are rarely used to predict long-term outcomes. This study assessed whether a single admission rotational thromboelastometry (ROTEM) test could independently pre...

Machine learning-enhanced normal tissue complication probability modeling for late sciatic nerve toxicity prediction in carbon-ion radiotherapy: model development and clinical validation.

Physics in medicine and biology
To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...

Machine learning-driven Diabetes Health Tracer (DHT): Optimizing prognosis using RaSK_GraDe and RaSK_GraDeL models.

PloS one
Diabetes mellitus presents a significant global health challenge, particularly in regions like Pakistan, India, and Bangladesh. Machine learning (ML) techniques offer promising solutions for diabetes prediction, surpassing traditional methods in reli...

Classification of images of bee pollen according to their producers.

PloS one
The food industry is witnessing a growing interest in pollen due to its nutritional and energy composition. Consumers of bee pollen are increasingly eager to learn about the origins of the products they purchase. Establishing the geographical origin ...

Development and validation of a bedside-available machine learning model to predict discrepancies between SaO₂ and SpO₂: Exploring factors related to the discrepancies.

PloS one
In critically ill patients, a discrepancy frequently exists between percutaneous oxygen saturation (SpO₂) and arterial blood oxygen saturation (SaO₂), which can lead to potential hypoxemia being overlooked. The aim of this study was to explore the fa...

Landslide susceptibility assessment via the information value-coupled machine learning models.

PloS one
Collapses and landslides are frequent in the southern mountainous areas of the economic zone on the northern slopes of the Tianshan Mountains in Xinjiang, and an accurate assessment of susceptibility can effectively avoid potential risks, which is cr...

Machine learning detects hidden treatment response patterns only in the presence of comprehensive clinical phenotyping.

PloS one
Inferential statistics traditionally used in clinical trials can miss relationships between clinical phenotypes and treatment responses. We simulated a randomised clinical trial to explore how gradient boosting (XGBoost) machine learning compares wit...

Subvisual imaging signals as biomarkers of impending lung metastasis: A multicenter pan-cancer study.

European journal of cancer (Oxford, England : 1990)
STUDY AIM: Early detection of distant metastases is crucial, but current imaging detects them only when radiographically visible. This study reported subvisual chest CT signals could serve as early biomarkers for impending lung metastasis before radi...

Machine Learning Modeling for ABC Transporter Efflux and Inhibition: Data Curation, Model Development, and New Compound Interaction Predictions.

Molecular pharmaceutics
In recent years, multiple computational studies have used machine learning models to predict substrate binding and inhibition of ATP-binding cassette (ABC) transporters. However, many of these studies relied on relatively small training sets with lim...