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Mitigating Bias in Clinical Machine Learning Models
Purpose of reviewIdentifying the risk for and addressing bias in clinical machine learning models is essential to reap its full benefits and ensure...
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Bridging the Worlds of Pharmacometrics and Machine Learning
Precision medicine requires individualized modeling of disease and drug dynamics, with machine learning-based computational techniques gaining...
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Integrated machine learning and deep learning for predicting diabetic nephropathy model construction, validation, and interpretability
ObjectiveTo construct a risk prediction model for assisted diagnosis of Diabetic Nephropathy (DN) using machine learning algorithms, and to validate...
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Machine learning and deep learning for classifying the justification of brain CT referrals
ObjectivesTo train the machine and deep learning models to automate the justification analysis of radiology referrals in accordance with iGuide...
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Machine Learning and Artificial Intelligence to Improve Interpretation of Urodynamics
Purpose of ReviewWe sought to review and discuss the current state and future trajectory of machine learning in interpretation of urodynamics...
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Machine Learning to Predict Adult Cochlear Implant Candidacy
Purpose of ReviewThe purpose of this review is to summarize candidacy criteria and commonly used referral guidelines for adult cochlear implant (CI)...
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Machine learning algorithm predicts urethral stricture following transurethral prostate resection
PurposeTo predict the post transurethral prostate resection(TURP) urethral stricture probability by applying different machine learning algorithms...
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Utilization of machine learning for dengue case screening
Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern....
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Exploring the potential of machine learning in gynecological care: a review
Gynecological health remains a critical aspect of women’s overall well-being, with profound implications for maternal and reproductive outcomes. This...
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Systematic review using a spiral approach with machine learning
With the accelerating growth of the academic corpus, doubling every 9 years, machine learning is a promising avenue to make systematic review...
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Reassessing acquired neonatal intestinal diseases using unsupervised machine learning
BackgroundAcquired neonatal intestinal diseases have an array of overlap** presentations and are often labeled under the dichotomous classification...
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Machine learning, deep learning and hernia surgery. Are we pushing the limits of abdominal core health? A qualitative systematic review
IntroductionThis systematic review aims to evaluate the use of machine learning and artificial intelligence in hernia surgery.
MethodsThe PRISMA...
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A retrospective study on machine learning-assisted stroke recognition for medical helpline calls
Advanced stroke treatment is time-dependent and, therefore, relies on recognition by call-takers at prehospital telehealth services to ensure fast...
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Machine learning based on SEER database to predict distant metastasis of thyroid cancer
ObjectiveDistant metastasis of thyroid cancer often indicates poor prognosis, and it is important to identify patients who have developed distant...
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Machine learning methods for adult OSAHS risk prediction
BackgroundObstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was...
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Machine learning algorithms for predicting COVID-19 mortality in Ethiopia
BackgroundCoronavirus disease 2019 (COVID-19), a global public health crisis, continues to pose challenges despite preventive measures. The daily...
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Application of machine-learning model to optimize colonic adenoma detection in India
AimsThere is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at develo** a...
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Machine learning and deep learning enabled age estimation on medial clavicle CT images
The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine...
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Machine learning applications on neonatal sepsis treatment: a sco** review
IntroductionNeonatal sepsis is a major cause of health loss and mortality worldwide. Without proper treatment, neonatal sepsis can quickly develop...
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Informing immunotherapy with multi-omics driven machine learning
Progress in sequencing technologies and clinical experiments has revolutionized immunotherapy on solid and hematologic malignancies. However, the...
