AIMC Topic: Humans

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Machine Learning Reveals Demographic Disparities in Palliative Care Timing Among Patients With Traumatic Brain Injury Receiving Neurosurgical Consultation.

Neurocritical care
BACKGROUND: Timely palliative care (PC) consultations offer demonstrable benefits for patients with traumatic brain injury (TBI), yet their implementation remains inconsistent. This study employs machine learning methods to identify distinct patient ...

Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.

Applied ergonomics
The performance of machine learning (ML) algorithms is dependent on which dataset it has been trained on. While ML algorithms are increasingly used for lift risk assessment, many algorithms are often trained and tested on controlled simulation datase...

[Current status and outlooks of acupuncture research driven by machine learning].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
The machine learning is used increasingly and widely in acupuncture prescription optimization, intelligent treatment and precision medicine, and has obtained a certain achievement. But, there are still some problems remained to be solved such as the ...

FedPD: Defending federated prototype learning against backdoor attacks.

Neural networks : the official journal of the International Neural Network Society
Federated Learning (FL) is an efficient, distributed machine learning paradigm that enables multiple clients to jointly train high-performance deep learning models while maintaining training data locally. However, due to its distributed computing nat...

Robust long-tailed recognition with distribution-aware adversarial example generation.

Neural networks : the official journal of the International Neural Network Society
Confronting adversarial attacks and data imbalances, attaining adversarial robustness under long-tailed distribution presents a challenging problem. Adversarial training (AT) is a conventional solution for enhancing adversarial robustness, which gene...

Enhancing thin slice 3D T2-weighted prostate MRI with super-resolution deep learning reconstruction: Impact on image quality and PI-RADS assessment.

Magnetic resonance imaging
PURPOSES: This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the image quality of ...

Establishment of multiple machine learning prognostic model for gene differences between primary tumors and lymph nodes in luminal breast cancer.

Breast cancer research and treatment
BACKGROUND: This study aimed to explore the correlation between primary tumors (PT) and paired metastatic lymph nodes (LN) and to develop a predictive model to provide evidence for forecasting patient prognoses.

Subtyping strokes using blood-based protein biomarkers: A high-throughput proteomics and machine learning approach.

European journal of clinical investigation
BACKGROUND: Rapid diagnosis of stroke and its subtypes is critical in early stages. We aimed to discover and validate blood-based protein biomarkers to differentiate ischemic stroke (IS) from intracerebral haemorrhage (ICH) using high-throughput prot...

Automated Neuroprognostication Via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy.

Annals of neurology
OBJECTIVES: Neonatal hypoxic-ischemic encephalopathy is a serious neurologic condition associated with death or neurodevelopmental impairments. Magnetic resonance imaging (MRI) is routinely used for neuroprognostication, but there is substantial subj...

Recent advances on artificial intelligence-based approaches for food adulteration and fraud detection in the food industry: Challenges and opportunities.

Food chemistry
Food adulteration is the deceitful practice of misleading consumers about food to profit from it. The threat to public health and food quality or nutritional valuable make it a major issue. Food origin and adulteration should be considered to safegua...