AIMC Topic: Humans

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Machine Learning Models for Predicting Sudden Sensorineural Hearing Loss Outcome: A Systematic Review.

The Annals of otology, rhinology, and laryngology
BACKGROUND: Machine Learning models have been applied in various healthcare fields, including Audiology, to predict disease outcomes. The prognosis of sudden sensorineural hearing loss is difficult to predict due to the variable course of the disease...

The role of innovative technologies in reducing health system inequity.

Healthcare management forum
The scarcity of Health Human Resources (HHR), regional disparities, and decentralized healthcare systems have profoundly affected health equity in Canada. Adequate HHR allocation is essential for equitable healthcare delivery, and the COVID-19 pandem...

Radiomics-based Machine Learning to Predict the Recurrence of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

Academic radiology
RATIONALE AND OBJECTIVES: Recurrence of hepatocellular carcinoma (HCC) is a major concern in its management. Accurately predicting the risk of recurrence is crucial for determining appropriate treatment strategies and improving patient outcomes. A ce...

Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard.

Current problems in diagnostic radiology
Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and B...

SaRF: Saliency regularized feature learning improves MRI sequence classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning based medical image analysis technologies have the potential to greatly improve the workflow of neuro-radiologists dealing routinely with multi-sequence MRI. However, an essential step for current deep learning...

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers r...

Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review.

Heart failure reviews
The aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy ...

Machine learning in medication prescription: A systematic review.

International journal of medical informatics
BACKGROUND: Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications "off-label" as chil...

Attention2Minority: A salient instance inference-based multiple instance learning for classifying small lesions in whole slide images.

Computers in biology and medicine
Multiple instance learning (MIL) models have achieved remarkable success in analyzing whole slide images (WSIs) for disease classification problems. However, with regard to giga-pixel WSI classification problems, current MIL models are often incapabl...

Cybersecurity in neural interfaces: Survey and future trends.

Computers in biology and medicine
With the joint advancement in areas such as pervasive neural data sensing, neural computing, neuromodulation and artificial intelligence, neural interface has become a promising technology facilitating both the closed-loop neurorehabilitation for neu...