AIMC Topic: Female

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Prospective prediction of anxiety onset in the Canadian longitudinal study on aging (CLSA): A machine learning study.

Journal of affective disorders
BACKGROUND: Anxiety disorders are among the most common mental health disorders in the middle aged and older population. Because older individuals are more likely to have multiple comorbidities or increased frailty, the impact of anxiety disorders on...

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of pa...

BC-QNet: A quantum-infused ELM model for breast cancer diagnosis.

Computers in biology and medicine
The timely and accurate diagnosis of breast cancer is pivotal for effective treatment, but current automated mammography classification methods have their constraints. In this study, we introduce an innovative hybrid model that marries the power of t...

Autism spectrum disorder diagnosis with EEG signals using time series maps of brain functional connectivity and a combined CNN-LSTM model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: People with autism spectrum disorder (ASD) often have cognitive impairments. Effective connectivity between different areas of the brain is essential for normal cognition. Electroencephalography (EEG) has been widely used in...

Combined blood Neurofilament light chain and third ventricle width to differentiate Progressive Supranuclear Palsy from Parkinson's Disease: A machine learning study.

Parkinsonism & related disorders
INTRODUCTION: Differentiating Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) may be clinically challenging. In this study, we explored the performance of machine learning models based on MR imaging and blood molecular biomarkers i...

Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects.

Research in developmental disabilities
There is a growing debate among scholars regarding the impact of artificial intelligence (AI) on the employment opportunities and professional development of people with disability. Although there has been an increasing body of empirical research on ...

The effect of time normalization and biomechanical signal processing techniques of ground reaction force curves on deep-learning model performance.

Journal of biomechanics
Time-series data are common in biomechanical studies. These data often undergo pre-processing steps such as time normalization or filtering prior to use in further analyses, including deep-learning classification. In this context, it remains unclear ...

Temporal Relationship-Aware Treadmill Exercise Test Analysis Network for Coronary Artery Disease Diagnosis.

Sensors (Basel, Switzerland)
The treadmill exercise test (TET) serves as a non-invasive method for the diagnosis of coronary artery disease (CAD). Despite its widespread use, TET reports are susceptible to external influences, heightening the risk of misdiagnosis and underdiagno...

Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model.

BMC psychology
OBJECTIVES: COVID-19 epidemics often lead to elevated levels of depression. To accurately identify and predict depression levels in home-quarantined individuals during a COVID-19 epidemic, this study constructed a depression prediction model based on...