AIMC Topic: Algorithms

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Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Automatic High Tibial Osteotomy (HTO) landmark detection methods promise to improve the effectiveness and standardisation of HTO preoperative planning. Unfortunately, due to the limited number of HTO datasets, existing methods are less ro...

Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Journal of cataract and refractive surgery
PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.

Oropharyngeal Cancer Staging Health Record Extraction Using Artificial Intelligence.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Accurate, timely, and cost-effective methods for staging oropharyngeal cancers are crucial for patient prognosis and treatment decisions, but staging documentation is often inaccurate or incomplete. With the emergence of artificial intell...

[Application of CT Radiomics in Predicting Differentiation Level of Lung Adenocarcinoma].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: To investigate the value of prediction of the differentiation level in lung adenocarcinoma based on CT radiomics model.

Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

Bioinformatics (Oxford, England)
MOTIVATION: Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfa...

Tiberius: end-to-end deep learning with an HMM for gene prediction.

Bioinformatics (Oxford, England)
MOTIVATION: For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of...

Live-Donor Kidney Transplant Outcome Prediction (L-TOP) using artificial intelligence.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: Outcome prediction for live-donor kidney transplantation improves clinical and patient decisions and donor selection. However, the currently used models are of limited discriminative or calibration power and there is a critical need to im...

[ protein design in the age of artificial intelligence].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Proteins with specific functions and characteristics play a crucial role in biomedicine and nanotechnology. protein design enables the customization of sequences to produce proteins with desired structures that do not exist in the nature. In recent ...

[Study on predicting new onset heart failure events in patients with hypertrophic cardiomyopathy using machine learning algorithms based on clinical and magnetic resonance features].

Zhonghua xin xue guan bing za zhi
To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms. The study was a retrospective co...

Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets.

Briefings in bioinformatics
Modelling biological systems depends on the availability of data and components of the system at hand. As our understanding of these systems evolves, the ability to gradually refine models by adding new components of different formalisms covering sto...