AIMC Topic: Humans

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Development and validation of a machine learning model for predicting drug-drug interactions with oral diabetes medications.

Methods (San Diego, Calif.)
Diabetes management is often complicated by comorbidities, requiring complex medication regimens that increase the risk of drug-drug interactions (DDIs), potentially compromising treatment outcomes or causing toxicity. Although machine learning (ML) ...

Mitigating biases in feature selection and importance assessments in predictive models using LASSO regression.

Oral oncology
Yuan et al. developed a predictive model for early response using sub-regional radiomic features from multi-sequence MRI alongside clinical factors. However, biases in feature selection and assessment may lead to misleading conclusions regarding feat...

Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques.

Computers in biology and medicine
Gastric cancer represents a significant global health challenge with elevated incidence and mortality rates, highlighting the need for advancements in diagnostic and therapeutic strategies. This review paper addresses the critical need for a thorough...

Machine learning model identifies genetic predictors of cisplatin-induced ototoxicity in CERS6 and TLR4.

Computers in biology and medicine
BACKGROUND: Cisplatin-induced ototoxicity remains a significant concern in pediatric cancer treatment due to its permanent impact on quality of life. Previously, genetic association analyses have been performed to detect genetic variants associated w...

Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning.

ACS applied materials & interfaces
Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patient rehabilitation feedback, and telemedicine. However, the effective and stable acquisition and automatic analysis of gait information remain signific...

Mass Spectrometry Probe Combined with Machine Learning to Capture the Relationship between Metabolites and Mitochondrial Complex Activity at the Whole-Cell Level.

Analytical chemistry
Mitochondrial complex activity controls a multitude of physiological processes by regulating the cellular metabolism. Current methods for evaluating mitochondrial complex activity mainly focus on single metabolic reactions within mitochondria. These ...

Digital Psychiatry: Opportunities, Challenges, and Future Directions.

Journal of psychiatric practice
Recently, the field of psychiatry has experienced a transformative shift with the integration of digital tools into traditional therapeutic approaches. Digital psychiatry encompasses a wide spectrum of applications, ranging from digital phenotyping, ...

Advances in Imaging-Based Machine Learning and Therapeutic Technology in the Management of Retinal Diseases.

Medicina (Kaunas, Lithuania)
Retinal conditions like age-related macular degeneration (AMD), diabetic retinopathy, central serous chorioretinopathy (CSCR), and retinal vein occlusion can drastically affect a patient's quality of life [...].

DeepDualEnhancer: A Dual-Feature Input DNABert Based Deep Learning Method for Enhancer Recognition.

International journal of molecular sciences
Enhancers are cis-regulatory DNA sequences that are widely distributed throughout the genome. They can precisely regulate the expression of target genes. Since the features of enhancer segments are difficult to detect, we propose DeepDualEnhancer, a ...

Assessment of pencil beam scanning proton therapy beam delivery accuracy through machine learning and log file analysis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Comprehensive Quality Assurance (QA) protocols are necessary for complex beam delivery systems like Pencil Beam Scanning (PBS) proton therapy. This study focuses on automating the evaluation of beam delivery accuracy using irradiation log fi...