AIMC Topic: Female

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Clinical applications of radiomics and deep learning in breast and lung cancer: A narrative literature review on current evidence and future perspectives.

Critical reviews in oncology/hematology
Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging field in translational oncology. Radiomics has been investigated in several neoplastic malignancies as it might allow for a non-invasive tumour characteri...

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

Journal of neuroscience methods
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing m...

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.

Brain, behavior, and immunity
BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine...

Improving the diagnostic value of lineup rejections.

Cognition
Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an ...

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Applied psychology. Health and well-being
Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of li...

Computer-Aided Classification of Breast Lesions Based on US RF Time Series Using a Novel Machine Learning Approach.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: One of the most promising adjuncts for screening breast cancer is ultrasound (US) radio-frequency (RF) time series. It has the superiority of not requiring any supplementary equipment over other methods. This research aimed to propound a ...

Polyp detection with colonoscopy assisted by the GI Genius artificial intelligence endoscopy module compared with standard colonoscopy in routine colonoscopy practice (COLO-DETECT): a multicentre, open-label, parallel-arm, pragmatic randomised controlled trial.

The lancet. Gastroenterology & hepatology
BACKGROUND: Increased polyp detection during colonoscopy is associated with decreased post-colonoscopy colorectal cancer incidence and mortality. The COLO-DETECT trial aimed to assess the clinical effectiveness of the GI Genius intelligent endoscopy ...

What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson's disease from videos.

Parkinsonism & related disorders
BACKGROUND: Evaluation of disease severity in Parkinson's disease (PD) relies on motor symptoms quantification. However, during early-stage PD, these symptoms are subtle and difficult to quantify by experts, which might result in delayed diagnosis an...

Generalizability of electroencephalographic interpretation using artificial intelligence: An external validation study.

Epilepsia
OBJECTIVE: The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, ...