AIMC Topic: Humans

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Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Cell reports. Medicine
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in H...

PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification.

Journal of proteome research
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, d...

"Tom and Pepper Lab". Robotics for cognitive stimulation and social skills: A preliminary study.

Asian journal of psychiatry
Dementia affects over 55 million people globally, with early cognitive decline, such as Mild Cognitive Impairment (MCI), often preceding neurodegenerative diseases. This decline impairs memory, attention, and Theory of Mind (ToM). Early intervention ...

Machine learning-driven Raman spectroscopy: A novel approach to lipid profiling in diabetic kidney disease.

Nanomedicine : nanotechnology, biology, and medicine
Diabetes mellitus is a chronic metabolic disease that increasingly affects people every year. It is known that with its progression and poor management, metabolic changes can lead to organ dysfunctions, including kidneys. The study aimed to combine R...

Deep learning methods for proteome-scale interaction prediction.

Current opinion in structural biology
Proteome-scale interaction prediction is essential for understanding protein functions and disease mechanisms. Traditional experimental methods are often limited by scale and complexity, driving the need for computational approaches. Deep learning ha...

Artificial Intelligence In Health And Health Care: Priorities For Action.

Health affairs (Project Hope)
The field of artificial intelligence (AI) has entered a new cycle of intense opportunity, fueled by advances in deep learning, including generative AI. Applications of recent advances affect many aspects of everyday life, yet nowhere is it more impor...

Deep Learning-Based Assessment of Lip Symmetry for Patients With Repaired Cleft Lip.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
ObjectivePost-surgical lip symmetry assessment is a key indicator of cleft repair success. Traditional methods rely on distances between anatomical landmarks, which are impractical for video analysis and overlook texture and appearance. We propose an...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

Medicina (Kaunas, Lithuania)
: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on individuals' psychological states. Utilizing statistical methods and machine learning models, these studi...

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Sensors (Basel, Switzerland)
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...

Stacking Ensemble Deep Learning for Real-Time Intrusion Detection in IoMT Environments.

Sensors (Basel, Switzerland)
The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling advanced patient care through interconnected medical devices and systems. However, its critical role and sensitive data make it a prime target for cyber threats, requirin...