AIMC Topic: Humans

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Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

Annals of medicine
BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity.

Soft Robotics: A Route to Equality, Diversity, and Inclusivity in Robotics.

Soft robotics
Robotics is entering our daily lives. The discipline is increasingly crucial in fields such as agriculture, medicine, and rescue operations, impacting our food, health, and planet. At the same time, it is becoming evident that robotic research must e...

How perceived lack of benevolence harms trust of artificial intelligence management.

The Journal of applied psychology
As organizations continue to supplement and replace human management with artificial intelligence (AI), it is essential that we understand the factors that influence employees' trust in AI management. Across one preregistered field study, where we su...

CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.

Oral diseases
OBJECTIVE: In this study, our aim was to develop and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery.

CT-Net: an interpretable CNN-Transformer fusion network for fNIRS classification.

Medical & biological engineering & computing
Functional near-infrared spectroscopy (fNIRS), an optical neuroimaging technique, has been widely used in the field of brain activity recognition and brain-computer interface. Existing works have proposed deep learning-based algorithms for the fNIRS ...

HoopTransformer: Advancing NBA Offensive Play Recognition with Self-Supervised Learning from Player Trajectories.

Sports medicine (Auckland, N.Z.)
BACKGROUND AND OBJECTIVE: Understanding and recognizing basketball offensive set plays, which involve intricate interactions between players, have always been regarded as challenging tasks for untrained humans, not to mention machines. In this study,...

Artificial Intelligence Applications in Cytopathology: Current State of the Art.

Surgical pathology clinics
The practice of cytopathology has been significantly refined in recent years, largely through the creation of consensus rule sets for the diagnosis of particular specimens (Bethesda, Milan, Paris, and so forth). In general, these diagnostic systems h...

Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes.

Medicina clinica
BACKGROUND: Coronary heart disease is the leading cause of heart failure (HF), and tools are needed to identify patients with a higher probability of developing HF after an acute coronary syndrome (ACS). Artificial intelligence (AI) has proven to be ...

Clinicosocial determinants of hospital stay following cervical decompression: A public healthcare perspective and machine learning model.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
OBJECTIVE: Post-operative length of hospital stay (LOS) is a valuable measure for monitoring quality of care provision, patient recovery, and guiding hospital resource management. But the impact of patient ethnicity, socio-economic deprivation as mea...

Can machine learning predict late seizures after intracerebral hemorrhages? Evidence from real-world data.

Epilepsy & behavior : E&B
INTRODUCTION: Intracerebral hemorrhage represents 15 % of all strokes and it is associated with a high risk of post-stroke epilepsy. However, there are no reliable methods to accurately predict those at higher risk for developing seizures despite the...