AIMC Topic: Female

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Combining extreme learning machines using support vector machines for breast tissue classification.

Computer methods in biomechanics and biomedical engineering
In this paper, we present a new approach for breast tissue classification using the features derived from electrical impedance spectroscopy. This method is composed of a feature extraction method, feature selection phase and a classification step. Th...

[Enhancement of radiomics-based machine learning models for predicting efficacy of high-intensity focused ultrasound ablation of uterine fibroids using undersampling methods].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: To improve the accuracy of machine learning models for preoperative prediction of high-intensity focused ultrasound (HIFU) ablation efficacy for uterine fibroids by correcting class imbalance in small sample datasets using undersampling m...

Machine Learning-Based Prediction of Distant Recurrence Risk and Ribociclib Treatment Effect in HR+/HER2- Early Breast Cancer Using Real-World and NATALEE Data.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Despite current standard-of-care endocrine therapy, distant recurrence remains a concern for patients with hormone receptor-positive (HR+)/HER2- early breast cancer (EBC). Understanding individual recurrence risk would aid in clinical decisi...

The Association Between Psychotropic Medications and Cognitive Functioning in a Real-World Cohort of 869 Individuals with Schizophrenia.

Schizophrenia bulletin
BACKGROUND: Cognitive deficits are a central feature of schizophrenia for which there are not any established pharmacological treatments. Antipsychotics are the mainstay of schizophrenia therapy but the effects of these and other psychotropic medicat...

Mental Health Professionals' Perspectives on Digital Remote Monitoring in Services for People with Psychosis.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Digital remote monitoring (DRM) captures service users' health-related data remotely using devices such as smartphones and wearables. Data can be analyzed using advanced statistical methods (eg, machine learning) and shared...

The Retinal Age Gap as a Marker of Accelerated Aging in the Early Course of Schizophrenia.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Given the available findings confirming accelerated brain aging in schizophrenia (SZ), we conducted a study aimed at verifying whether quantitative retinal morphological data enable age prediction and whether schizophrenia ...

Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Minor physical abnormalities (MPAs) are neurodevelopmental markers that can be traced to prenatal events and may be significant features of early-onset schizophrenia (EOS). Therefore, our study aimed to (1) find the primary...

Artificial intelligence accelerates the interpretation of measurable residual B lymphoblastic leukemia by flow cytometry.

Blood advances
Measurable residual disease (MRD) assessment by flow cytometry (FC) plays an essential role in prognosis and therapy escalation of B-cell acute lymphoblastic leukemia (B-ALL). However, the high degree of expertise and manual analysis time required li...

The Hypno-PC: uncovering sleep dynamics through principal component analysis and hidden Markov modeling of electrophysiological signals.

Sleep
Manual sleep scoring segments sleep into discrete 30-s epochs (wake, non-rapid-eye-movement [NREM] 1-3, rapid-eye-movement [REM]), yet substantial evidence suggests that sleep unfolds as a continuous, microstate-rich process. Using a data-driven appr...