AIMC Topic: Neoplasms

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The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Biochimica et biophysica acta. Reviews on cancer
Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clinical trials. Recent advances in computational methods, notably causal artificial intelligence, and availability of rich clinico-genomic databases have ...

The potential of AI in cancer care and research.

Biochimica et biophysica acta. Reviews on cancer
Current applications of artificial intelligence (AI), machine learning, and deep learning in cancer research and clinical care are highly diverse-from aiding radiologists in reading medical images to predicting oncoprotein folding and dynamics. The l...

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...

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 ...

A review of AI and Data Science support for cancer management.

Artificial intelligence in medicine
INTRODUCTION: Thanks to improvement of care, cancer has become a chronic condition. But due to the toxicity of treatment, the importance of supporting the quality of life (QoL) of cancer patients increases. Monitoring and managing QoL relies on data ...

Application of nano-carbon and titanium clip combined labeling in robot-assisted laparoscopic transverse colon cancer surgery.

BMC surgery
BACKGROUND: Robot-assisted laparoscopic transverse colon tumor surgery requires precise tumor localization. The purpose of this study was to evaluate the safety and efficacy of nano-carbon and titanium clip combination labeling methods in robot-assis...

Permutation-based identification of important biomarkers for complex diseases via machine learning models.

Nature communications
Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods have been developed and widely used to alleviate some anal...

Aging-related markers in rat urine revealed by dynamic metabolic profiling using machine learning.

Aging
The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine le...

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

JNCI cancer spectrum
In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entire...

CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training.

BMC bioinformatics
BACKGROUND: The state-of-the-art deep learning based cancer type prediction can only predict cancer types whose samples are available during the training where the sample size is commonly large. In this paper, we consider how to utilize the existing ...