AIMC Topic: Female

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Generative artificial intelligence versus clinicians: Who diagnoses multiple sclerosis faster and with greater accuracy?

Multiple sclerosis and related disorders
BACKGROUND: Those receiving the diagnosis of multiple sclerosis (MS) over the next ten years will predominantly be part of Generation Z (Gen Z). Recent observations within our clinic suggest that younger people with MS utilize online generative artif...

Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after conventional therapy for patients with acute coronary syndrome (ACS). Timely identification of PR improves the risk stratification and prognosis of ACS ...

Ensemble of machine learning techniques to predict survival in kidney transplant recipients.

Computers in biology and medicine
Kidney transplant recipients face a high cardiovascular risk, which is a leading cause of death in this patient group. This article proposes the application of clustering techniques and feature selection to predict the survival outcomes of kidney tra...

The consequences of AI training on human decision-making.

Proceedings of the National Academy of Sciences of the United States of America
AI is now an integral part of everyday decision-making, assisting us in both routine and high-stakes choices. These AI models often learn from human behavior, assuming this training data is unbiased. However, we report five studies that show that peo...

An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements.

Sensors (Basel, Switzerland)
Stress has various impacts on the health of human beings. Recent success in wearable sensor development, combined with advancements in deep learning to automatically detect features from raw data, opens several interesting applications related to det...

Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.

Cells
Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming an...

Shaping future practices: German-speaking medical and dental students' perceptions of artificial intelligence in healthcare.

BMC medical education
BACKGROUND: The growing use of artificial intelligence (AI) in healthcare necessitates understanding the perspectives of future practitioners. This study investigated the perceptions of German-speaking medical and dental students regarding the role o...

Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.

BMC public health
BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle i...

Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.

Scientific reports
Patients with mental illnesses, particularly psychosis and obsessive‒compulsive disorder (OCD), frequently exhibit deficits in executive function and visuospatial memory. Traditional assessments, such as the Rey‒Osterrieth Complex Figure Test (RCFT),...

Advancements in triple-negative breast cancer sub-typing, diagnosis and treatment with assistance of artificial intelligence : a focused review.

Journal of cancer research and clinical oncology
Triple negative breast cancer (TNBC) is most aggressive type of breast cancer with multiple invasive sub-types and leading cause of women's death worldwide. Lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor...