AIMC Topic: Machine Learning

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Kvasir-Capsule, a video capsule endoscopy dataset.

Scientific data
Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates the promising ben...

Protein sequence design with deep generative models.

Current opinion in chemical biology
Protein engineering seeks to identify protein sequences with optimized properties. When guided by machine learning, protein sequence generation methods can draw on prior knowledge and experimental efforts to improve this process. In this review, we h...

Data-driven approaches to advance research and clinical care for pediatric cancer.

Biochimica et biophysica acta. Reviews on cancer
Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in u...

SolTranNet-A Machine Learning Tool for Fast Aqueous Solubility Prediction.

Journal of chemical information and modeling
While accurate prediction of aqueous solubility remains a challenge in drug discovery, machine learning (ML) approaches have become increasingly popular for this task. For instance, in the Second Challenge to Predict Aqueous Solubility (SC2), all gro...

Swarm Learning for decentralized and confidential clinical machine learning.

Nature
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an i...

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.

International journal of molecular sciences
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...

Cell morphology-based machine learning models for human cell state classification.

NPJ systems biology and applications
Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively forward (FSC) and side (SSC) scatter flow cytometry information. To generate training data, colorecta...

Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow.

Systematic reviews
BACKGROUND: Current text mining tools supporting abstract screening in systematic reviews are not widely used, in part because they lack sensitivity and precision. We set out to develop an accessible, semi-automated "workflow" to conduct abstract scr...