AIMC Topic: Machine Learning

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Machine Learning-Based Pathomics Signature for Perineural Invasion in Colorectal Cancer.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Perineural invasion (PNI) is strongly associated with poor clinical outcomes in colorectal cancer (CRC). However, no machine learning diagnostic model based on pathomics has been established for PNI detection in CRC. To address this issue,...

Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study.

Journal of medical systems
This study aimed to develop machine learning-based algorithms to assist physicians in ultrasound-guided localization of the cricoid cartilage (CC), thyroid cartilage (TC), and cricothyroid membrane (CTM) for cricothyroidotomy. Adult female participan...

On the effectiveness of network metrics on key class prediction: An empirical study.

PloS one
Key classes are the most important classes in a software system, which provide an excellent foundation for developers-especially those new to the field-to understand unfamiliar software systems. In the past decade, several key class prediction (KCP) ...

SHAP-enhanced machine learning identifies modifiable obesity predictors across adolescent weight groups: A 2021 YRBSS analysis.

PloS one
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...

Development and internal validation of multimodal machine learning models for predicting eligibility for mechanical thrombectomy in suspected stroke patients using routinely collected clinical and imaging data.

PloS one
BACKGROUND: Mechanical thrombectomy (MT) eligibility for acute ischemic stroke (AIS) patients depends upon clinical and advanced imaging assessments like CT perfusion (CTP). Assessment complexities and limited access to advanced imaging investigation...

From objective grouping to fuzzy reference intervals: A standardized machine learning approach for thyroid function tests.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Accurate interpretation of thyroid function tests (TFTs) requires reliable reference intervals (RIs). Indirect methods based on retrospective laboratory data are increasingly used, but current strategies face major limitations, including ...

Electrochemical "Super-Fingerprinting" in Combination with Machine Learning for the On-Site Detection of Illicit Drugs.

ACS sensors
On-site multidrug sensing remains challenging due to the complexity of real samples and the differing detection requirements of individual substances. In the current study, we present successful electrochemical multidrug detection that overcomes thes...

Machine Learning-Enhanced Analysis of miRNA Biomarkers for Accurate Breast Cancer Diagnosis Using DNA Seagrass.

Analytical chemistry
As potential biomarkers for breast cancer, microRNAs (miRNAs) have demonstrated significant promise in clinical applications. However, accurate miRNA-based breast cancer diagnosis is hindered by the lack of simple, ultrasensitive, and highly specific...

Real-time biofeedback monitoring rehabilitation of distal radius fracture.

Journal of neuroengineering and rehabilitation
BACKGROUND: Elderly patients often face challenges in recovering from distal radius fractures (DRFs), and inadequately guided rehabilitation may lead to delayed healing or secondary injury.

Machine learning-based estimation of the mild cognitive impairment stage using multimodal physical and behavioral measures.

Scientific reports
Mild cognitive impairment (MCI) is a prodromal stage of dementia, and its early detection is critical for improving clinical outcomes. However, current diagnostic tools such as brain magnetic resonance imaging (MRI) and neuropsychological testing hav...