AIMC Topic: Humans

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Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.

Mycopathologia
This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Give...

Intranasal vasopressin modulates resting state brain activity across multiple neural systems: Evidence from a brain imaging machine learning study.

Neuropharmacology
Arginine vasopressin (AVP), a neuropeptide with widespread receptors in brain regions important for socioemotional processing, is critical in regulating various mammalian social behavior and emotion. Although a growing body of task-based brain imagin...

Unsupervised Monocular Depth Estimation for Colonoscope System Using Feedback Network.

Sensors (Basel, Switzerland)
A colonoscopy is a medical examination used to check disease or abnormalities in the large intestine. If necessary, polyps or adenomas would be removed through the scope during a colonoscopy. Colorectal cancer can be prevented through this. However, ...

Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters.

Journal of cancer research and clinical oncology
PURPOSE: Microvascular invasion (MVI) is a critical determinant of the early recurrence and poor prognosis of patients with hepatocellular carcinoma (HCC). Prediction of MVI status is clinically significant for the decision of treatment strategies an...

Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Neuroradiology
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).

Machine Learning and Surgical Outcomes Prediction: A Systematic Review.

The Journal of surgical research
BACKGROUND: Machine learning (ML) has garnered increasing attention as a means to quantitatively analyze the growing and complex medical data to improve individualized patient care. We herein aim to critically examine the current state of ML in predi...

Core services that power AI-driven transformation in cancer research and care.

Biochimica et biophysica acta. Reviews on cancer
This review captures some key lessons learned in the course of helping some of America's leading healthcare AI innovators achieve scale and sustained impact in complex research and care delivery ecosystems. AI innovators may find it useful to access ...

Effectiveness and Safety of Moxibustion Robots on Primary Dysmenorrhea: A Randomized Controlled Pilot Trial.

Chinese journal of integrative medicine
OBJECTIVE: To conduct a pilot trial to explore the effectiveness and safety of moxibustion robots in treating primary dysmenorrhea (PD) and evaluate its feasibility in clinic.

Uncertainty-aware temporal self-learning (UATS): Semi-supervised learning for segmentation of prostate zones and beyond.

Artificial intelligence in medicine
Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and peripheral zone (PZ). However, when targeting a fine-grained segmentatio...

Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review.

International journal of medical informatics
BACKGROUND AND OBJECTIVES: Sepsis is a life-threatening condition that is associated with increased mortality. Artificial intelligence tools can inform clinical decision making by flagging patients at risk of developing infection and subsequent sepsi...