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Comprehensive identification of immune-related biomarkers and therapeutic targets in preeclampsia: integrative bioinformatics and experimental validation.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a serious hypertensive complication during pregnancy characterized by immune dysregulation and vascular dysfunction, however, the precise molecular mechanisms and effective therapeutic strategies remain unclear. This ...

A deep learning-enriched framework for analyzing brain functional connectivity.

Scientific reports
Cognitive and motor functions require a coordinated communication among brain regions, with the directionality of interactions playing a key role, as the brain relies on functional asymmetries of reciprocal connections. Predictive models based on dee...

Novel Prototype and Exemplar (NPE) database: A set of 2700 novel 3D images with viewpoint and shape variations.

Behavior research methods
Many studies have used images of novel objects as experimental materials. Existing novel object databases do not provide diverse exemplars, and many studies need to manipulate or examine the diversity of exemplars. To fill this gap in experimental ma...

Clinician perspectives on explainability in AI-driven closed-loop neurotechnology.

Scientific reports
Artificial Intelligence (AI) holds promise for advancing the field of neurotechnology and accelerating its clinical translation. AI-driven clinical neurotechnologies leverage the power of non-linear algorithms to analyze complex brain data and enable...

Transfer learning-enhanced CNN model for integrative ultrasound and biomarker-based diagnosis of polycystic ovarian disease.

Scientific reports
Polycystic Ovarian Disease (PCOD), also known as Polycystic Ovary Syndrome (PCOS), is a prevalent hormonal and metabolic condition primarily affecting women of reproductive age worldwide. It is typically marked by disrupted ovulation, an increase in ...

Hierarchical attention enhanced deep learning achieves high precision motor imagery classification in brain computer interfaces.

Scientific reports
Motor imagery-based Brain-Computer Interfaces (BCIs) hold transformative potential for individuals with severe motor impairments, yet their clinical deployment remains constrained by the inherent complexity of electroencephalographic (EEG) signal dec...

Estimation of sexual dimorphism of adult human mandibles of South Indian origin using non-metric parameters and machine learning classification algorithms.

Scientific reports
The mandible is one of the most reliable in sex determination in forensic anthropology. The shape of the mandible provides valuable information regarding the male and female distinctions. Machine learning algorithms are widely used for various applic...

Identifying prenatal risk factors of postpartum depression with machine learning.

Scientific reports
Postpartum depression (PPD), a common mental illness among mothers, can affect the well-being of both mothers and their children. Early intervention is essential but hindered by difficulties in identifying at-risk women, as it remains unclear how soo...

Application of machine learning models for predicting depression among older adults with non-communicable diseases in India.

Scientific reports
Depression among older adults is a critical public health issue, particularly when coexisting with non-communicable diseases (NCDs). In India, where population ageing and NCDs burden are rising rapidly, scalable data-driven approaches are needed to i...

Creative experiences and brain clocks.

Nature communications
Creative experiences may enhance brain health, yet metrics and mechanisms remain elusive. We characterized brain health using brain clocks, which capture deviations from chronological age (i.e., accelerated or delayed brain aging). We combined M/EEG ...