AIMC Topic: Adult

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Machine learning improves detection of alpha thalassemia carriers compared to clinical features.

Scientific reports
Alpha-thalassemia is a widespread genetic disorder, and accurately distinguishing between alpha-plus (α⁺) and alpha-zero (α⁰) types is critical for effective screening and management. This study developed and evaluated machine learning models to clas...

L-SHADE optimized learning framework for sEMG hand gesture recognition.

Scientific reports
In recent years, Hand Gesture Recognition (HGR) devices have been designed to recognize gestures in real time using machine-learning classifiers (MLCs). However, the performance of these classifiers heavily relies on the tuning of their hyperparamete...

CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.

Scientific data
Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...

Exploring the impact mechanisms of EEG signals and emotional intelligence levels on language learning efficiency.

Scientific reports
Improving language learning through a better understanding of how brain activity and emotional intelligence interact is a promising research direction with practical value in education. Traditional methods in this area often use static models, which ...

Individual differences in anthropomorphism help explain social connection to AI companions.

Scientific reports
People increasingly use conversational AI for support and companionship. Yet, current discourse on AI companions reveals a stark divide: some scholars argue that feeling connected to AI is impossible due to AI's inability to experience emotions, whil...

Efficient elastic tissue motions indicate general motor skill.

Scientific reports
Insights into the general nature of motor skill could fundamentally change how we develop movement abilities, with implications for musculoskeletal well-being and injury. Here, we sought to identify indicators of general motor skill-those shared by e...

Prognostic value of admission ROTEM in trauma: enhancing 30-day all-cause mortality prediction using machine learning.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Haemorrhage is a leading cause of trauma death, yet early coagulation markers are rarely used to predict long-term outcomes. This study assessed whether a single admission rotational thromboelastometry (ROTEM) test could independently pre...

Machine learning-enhanced normal tissue complication probability modeling for late sciatic nerve toxicity prediction in carbon-ion radiotherapy: model development and clinical validation.

Physics in medicine and biology
To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...

Subvisual imaging signals as biomarkers of impending lung metastasis: A multicenter pan-cancer study.

European journal of cancer (Oxford, England : 1990)
STUDY AIM: Early detection of distant metastases is crucial, but current imaging detects them only when radiographically visible. This study reported subvisual chest CT signals could serve as early biomarkers for impending lung metastasis before radi...

A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region.

Scientific reports
Improving accuracy and timeliness for osteoporosis diagnosis could help prevent fragility fractures, morbidity, and mortality for older individuals. Osteoporosis is an often silent health condition, especially as regards vertebral fractures, and WHO ...