AIMC Topic: Middle Aged

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Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysis.

European journal of radiology
PURPOSE: For patients suffering from differentiated thyroid cancer (DTC), several clinical, laboratory, and pathological features (including patient age, tumor size, extrathyroidal extension, or serum thyroglobulin levels) are currently used to ident...

Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach.

The Journal of infection
OBJECTIVES: Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as a mild febrile illness, some progress to life-threatening severe dengue (SD). Early intervention is ...

Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests.

BMC medical informatics and decision making
Hyperuricemia has seen a continuous increase in incidence and a trend towards younger patients in recent years, posing a serious threat to human health and highlighting the urgency of using technological means for disease risk prediction. Existing ri...

Subphenotyping prone position responders with machine learning.

Critical care (London, England)
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a heterogeneous condition with varying response to prone positioning. We aimed to identify subphenotypes of ARDS patients undergoing prone positioning using machine learning and assess their a...

AI-ready rectal cancer MR imaging: a workflow for tumor detection and segmentation.

BMC medical imaging
BACKGROUND: Magnetic Resonance (MR) imaging is the preferred modality for staging in rectal cancer; however, despite its exceptional soft tissue contrast, segmenting rectal tumors on MR images remains challenging due to the overlapping appearance of ...

Optimized hybrid machine learning framework for early diabetes prediction using electrogastrograms.

Scientific reports
In recent years, diabetes has become a global public health problem, and it is reported that the migrant Indians have more prevalence rate of Type-II diabetes. Also, the type-II diabetes in Indians are increased to a large extent due to modern lifest...

Comparative analysis of deep learning architectures for breast region segmentation with a novel breast boundary proposal.

Scientific reports
Segmentation of the breast region in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for the automatic measurement of breast density and the quantitative analysis of imaging findings. This study aims to compare various dee...

Biological age prediction using a DNN model based on pathways of steroidogenesis.

Science advances
Aging involves the progressive accumulation of cellular damage, leading to systemic decline and age-related diseases. Despite advances in medicine, accurately predicting biological age (BA) remains challenging due to the complexity of aging processes...

Developing a machine learning-based predictive model for levothyroxine dosage estimation in hypothyroid patients: a retrospective study.

Frontiers in endocrinology
Hypothyroidism, a common endocrine disorder, has a high incidence in women and increases with age. Levothyroxine (LT4) is the standard therapy; however, achieving clinical and biochemical euthyroidism is challenging. Therefore, developing an accurate...

Exploring predictors of insomnia severity in shift workers using machine learning model.

Frontiers in public health
INTRODUCTION: Insomnia in shift workers has distinctive features due to circadian rhythm disruption caused by reversed or unstable sleep-wake cycle work schedules. While previous studies have primarily focused on a limited number of predictors for in...