AIMC Topic: Algorithms

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How large is the universe of RNA-like motifs? A clustering analysis of RNA graph motifs using topological descriptors.

PLoS computational biology
Identifying novel and functional RNA structures remains a significant challenge in RNA motif design and is crucial for developing RNA-based therapeutics. Here we introduce a computational topology-based approach with unsupervised machine-learning alg...

Applying binary mixed model to predict knee osteoarthritis pain.

PloS one
Data used to understand knee osteoarthritis (KOA) often involves knee-level, rather than person-level information. Failure to account for the correlation between joints within a person may lead to inaccurate inferences. The aim of this study was to d...

Driven early detection of chronic kidney cancer disease based on machine learning technique.

PloS one
In recent times, chronic kidney cancer has been considered a significant cause of cancer, and Renal Cell Carcinoma (RCC) has become a significant prevalent among various kidney cancer conditions. The analysis of kidney cancer, an important and often ...

Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods.

PloS one
In complex geological environments, the morphology, orientation and distribution characteristics of cracks in the rock directly affect the stability assessment for rock masses and engineering safety decisions. However, the traditional manual interpre...

Deep siamese residual support vector machine with applications to disease prediction.

Computers in biology and medicine
Support Vector Machines (SVMs) excel in classification and regression tasks involving high-dimensional nonlinear data, boasting high accuracy, strong generalization ability, and robust performance. Particularly noteworthy is their outstanding perform...

A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study.

World journal of emergency surgery : WJES
BACKGROUND: Accurately identifying difficult laparoscopic cholecystectomy (DLC) preoperatively remains a clinical challenge. Previous studies utilizing clinical variables or morphological imaging markers have demonstrated suboptimal predictive perfor...

Characterizing individual and methodological risk factors for survey non-completion using machine learning: findings from the U.S. Millennium Cohort Study.

BMC medical research methodology
BACKGROUND: Missing survey data can threaten the validity and generalizability of findings from longitudinal cohort studies. Respondent characteristics and survey attributes may contribute to patterns of survey non-completion, a form of missing data ...

Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity.

Nature communications
Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. Howe...

Generative AI enables medical image segmentation in ultra low-data regimes.

Nature communications
Semantic segmentation of medical images is pivotal in applications like disease diagnosis and treatment planning. While deep learning automates this task effectively, it struggles in ultra low-data regimes for the scarcity of annotated segmentation m...

Contrastive learning enhanced pseudo-labeling for unsupervised domain adaptation in person re-identification.

PloS one
Person re-identification (ReID) technology has many applications in intelligent surveillance and public safety. However, the domain difference between the source and target domains makes the generalization ability of the model extremely challenging. ...