Leukemia

Imaging-Based Outcome Prediction of Acute Intracerebral Hemorrhage.

We hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scans of patients with acute intracerebral hemorrhage (ICH). This retrospective multicenter cohort study analyzed 520 non-enhanced CT scans and clinical data of patients with acute spontaneous ICH. Clinical outcome at hospital discharge was dichotomized into good outcome and poor outcome using different...

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure food safety and prevent public health problems. Raman spectroscopy, a label-free, highly sensitive and dependable technology has attracted more and more attention in the field of diagnosing food-borne pathogens in recent years. In the research, 15,890 single-cell Raman spectra of 23 common strains fr...

Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition.

In this work, we aim to address the problem of human interaction recognition in videos by exploring the long-term inter-related dynamics among multipl...

Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and radiation treatment planning (RTP). Disadvantages of...

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.

Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging agents is quite challenging. Age-associated geneti...

Radiomics to better characterize small renal masses.

PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools to extract objective information from standard ima...

A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.

Machine Learning research applied to the medical field is increasing. However, few of the proposed approaches are actually deployed in clinical settin...

Artificial immune system features added to breast cancer clinical data for machine learning (ML) applications.

We here propose a new method of combining a mathematical model that describes a chemotherapy treatment for breast cancer with a machine-learning (ML) ...

Improving Global Healthcare and Reducing Costs Using Second-Generation Artificial Intelligence-Based Digital Pills: A Market Disruptor.

Improving global health requires making current and future drugs more effective and affordable. While healthcare systems around the world are faced w...

Dynamics of Systemic Inflammation as a Function of Developmental Stage in Pediatric Acute Liver Failure.

The Pediatric Acute Liver Failure (PALF) study is a multicenter, observational cohort study of infants and children diagnosed with this complex clinic...

Computer-aided diagnosis based on hand thermal, RGB images, and grip force using artificial intelligence as screening tool for rheumatoid arthritis in women.

Rheumatoid arthritis (RA) is an autoimmune disorder that typically affects people between 23 and 60 years old causing chronic synovial inflammation, s...

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.

The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the ana...

Utilization of circulating cell-free DNA profiling to guide first-line chemotherapy in advanced lung squamous cell carcinoma.

Platinum-based chemotherapy is one of treatment mainstay for patients with advanced lung squamous cell carcinoma (LUSC) but it is still a "one-size f...

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRL...

Increased Thyroid-Hormone Requirements Consistent With Type 3 Deiodinase Induction Related to Ibrutinib in a Thyroidectomized Woman.

OBJECTIVE: Tyrosine-kinase inhibitors (TKIs) are chemotherapeutic agents associated with increased thyroid-hormone requirements and altered deiodinase...

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.

The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Res...

Development of a quantitative systems pharmacology model of chronic kidney disease: metabolic bone disorder.

Chronic kidney disease mineral bone disorder (CKD-MBD) is a virtually universal complication of kidney diseases, starting early in the course of disea...

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors.

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning ...

Characterization of isolated compounds from spp. and their biological activity as anticancer molecules.

The genus is well known for its medicinal benefits from time immemorial. The present work reported the health-promoting properties of the biological...

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans.

The temporal bone is a part of the lateral skull surface that contains organs responsible for hearing and balance. Mastering surgery of the temporal b...