AIMC Topic: Humans

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Machine learning in understanding environmental variability of vibriosis in coastal waters.

Applied and environmental microbiology
comprise ecologically significant bacteria that thrive in warm, moderately saline water, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, . infections have been reported more frequently and ove...

Machine Learning on the Impacts of Mutations in the SARS-CoV-2 Spike RBD on Binding Affinity to Human ACE2 Based on Deep Mutational Scanning Data.

Biochemistry
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to accumulate mutations in the spike receptor-binding domain (RBD) region, leading to the emergence of new variants that potentially change the binding affinity for the human angi...

JointDiffusion: Joint representation learning for generative, predictive, and self-explainable AI in healthcare.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Joint machine learning models that allow synthesizing and classifying data often offer uneven performance between those tasks or are unstable to train. In this work, we depart from a set of empirical observations that indicate the usefulness of inter...

Comprehensive integration of single-cell and bulk transcriptome to reveal plasma cell heterogeneity and a prognosis signature in head and neck squamous cell carcinoma.

Oral oncology
Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a low five-year survival rate, emphasising the urgent need for effective prognostic biomarkers to guide patient stratification and personalised treatment. Plasma cells (PCs)...

Predicting fracture toughness of human cortical bone from donors with and without type 2 diabetes using Raman spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Type 2 diabetes mellitus (T2DM) is associated with increased skeletal fragility, yet standard clinical assessments often fail to detect diabetes-induced changes in bone quality. Raman spectroscopy (RS), a label-free and non-destructive technique, off...

Generative Artificial Intelligence (AI) to Uncover Insights From Breast Cancer Patients' Perceptions to Mindfulness-Based Stress Reduction (MBSR) Interventions.

Holistic nursing practice
The study's central objective is to harness the power of generative Artificial Intelligence (AI), in particular based on Large Language Models, as a valuable resource for delving deeper into the insights offered by patients with breast cancer (BC) wh...

Enhancing cardiac function assessment: Developing and validating a domain adaptive framework for automating the segmentation of echocardiogram videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Accurate segmentation of echocardiographic images is essential for assessing cardiac function, particularly in calculating key metrics such as ejection fraction. However, challenges such as domain discrepancy, noisy data, anatomical varia...

Ever-Increasing Role of Computational Tools in Solid-State Pharmaceutics: Advancing Drug Development with Enhanced Molecular Understanding and Risk Assessment.

Molecular pharmaceutics
The field of solid-state pharmaceutics comprises a broad range of investigations into various structural aspects of pharmaceutical solids, establishing a rational structure-property correlation. These solid systems allow the tunability of the physico...

Umami-Transformer: A deep learning framework for high-precision prediction and experimental validation of umami peptides.

Food chemistry
In food field, both identification of umami peptides and their sensory evaluation are limited by low efficiency of traditional methods and subjectivity of human-based assessments. To overcome these issues, Umami-Transformer was developed by integrati...