AIMC Topic: Humans

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SimTA++: Simple attention neural network for clinical asynchronous time series.

Neural networks : the official journal of the International Neural Network Society
The task of modeling asynchronous time series data in clinical practice is a formidable challenge, made even more difficult by the multi-modal and irregular nature of real-world medical time series data. Despite advances in deep learning for sequenti...

Discovery of milk-derived antimicrobial peptides in human milk by DeepMAMP based on peptidomics technology and deep learning method.

Food chemistry
Milk-derived antimicrobial peptides (MAMPs) in human milk (HMAMPs) play an important role in the nutrition and the immune system construction of newborns. Current AMP prediction models cannot accurately predict HMAMPs, thus high-throughput and target...

Detection of breast cancer using fractional discrete sinc transform based on empirical Fourier decomposition.

Bio-medical materials and engineering
Breast cancer is the most common cause of death among women worldwide. Early detection of breast cancer is important; for saving patients' lives. Ultrasound and mammography are the most common noninvasive methods for detecting breast cancer. Computer...

Selection of representative electrodes for stereoscopic visual comfort studies in conjunction with brain mechanism analysis.

Brain research
The widespread use of 3D stereoscopic technology has drawn attention to the problem of visual discomfort, several studies have used EEG to assess visual comfort and discomfort phenomena, but there is a lack of scientific basis for the selection of el...

Latest Advances in the Treatment of Patients with Acute Respiratory Distress Syndrome.

Critical care nursing clinics of North America
Acute respiratory distress syndrome (ARDS) is a life-threatening condition characterized by severe inflammation and impaired gas exchange, leading to hypoxemic respiratory failure. It significantly impacts patients by increasing morbidity, mortality,...

Zero- and few-shot Named Entity Recognition and Text Expansion in medication prescriptions using large language models.

Artificial intelligence in medicine
Medication prescriptions in electronic health records (EHR) are often in free-text and may include a mix of languages, local brand names, and a wide range of idiosyncratic formats and abbreviations. Large language models (LLMs) have shown a promising...

Interpretable Machine Learning approach for predicting clinically significant suicide risk: A case study of patients with major depressive disorder in Greece.

Psychiatry research
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...

Artificial intelligence and perspective for rare genetic kidney diseases.

Kidney international
The integration of big data and artificial intelligence (AI) has revolutionized biomedicine, enhancing our understanding of diseases and health care practices. Although AI has shown remarkable success in some medical fields, its application in nephro...

Artificial intelligence-driven discovery of novel scaffolds for selective TLR7 antagonists and their application in enhancing mRNA translation efficiency.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Toll-like receptor 7 (TLR7) is crucial in the innate immune response, responsible for recognizing single-stranded RNA from external pathogens and initiating the production of inflammatory cytokines and type I interferons. Despite the potential therap...

PMFF-Net: A deep learning-based image classification model for UIP, NSIP, and OP.

Computers in biology and medicine
BACKGROUND: High-resolution computed tomography (HRCT) is helpful for diagnosing interstitial lung diseases (ILD), but it largely depends on the experience of physicians. Herein, our study aims to develop a deep-learning-based classification model to...