Leukemia

Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population.

Reference intervals (RIs) for clinical laboratory values are extremely important for diagnostics and...

Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

This paper reported a micro flow cytometer capable of high-throughput characterization of single-cel...

All-Fabric Capacitive Pressure Sensors with Piezoelectric Nanofibers for Wearable Electronics and Robotic Sensing.

Flexible pressure sensors are increasingly sought after for applications ranging from physiological ...

Deep learning-assisted high-content screening identifies isoliquiritigenin as an inhibitor of DNA double-strand breaks for preventing doxorubicin-induced cardiotoxicity.

BACKGROUND: Anthracyclines including doxorubicin are essential components of many cancer chemotherap...

MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.

The number of studies on deep learning for medical diagnosis is expanding, and these systems are oft...

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.

BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC)...

Optimization of adaptation parameters from adhesion cell culture in serum-containing media to suspension in chemically defined media by superlative box design.

A new design of experiments-superlative box design (SBD), was adopted to optimize the adaptation of ...

An automatic progressive chromosome segmentation approach using deep learning with traditional image processing.

The fully automatic chromosome analysis system plays an important role in the detection of genetic d...

Methods for cell-type annotation on scRNA-seq data: A recent overview.

The evolution of single-cell technology is ongoing, continually generating massive amounts of data t...

Re: Post-chemotherapy robot-assisted retroperitoneal lymph node dissection for metastatic germ cell tumors: safety and perioperative outcomes. World J Urol. 2023 Jul 28. doi: 10.1007/s00345-023-04536-3.

Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing.

This paper discusses the challenges of producing CAR-T cells for cancer treatment and the potential ...

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.

OBJECTIVES: The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predict...

Study on the allosteric activation mechanism of SHP2 elastic network models and neural relational inference molecular dynamics simulation.

As a ubiquitous protein tyrosine phosphatase, SHP2 is involved in PD-1/PD-L1 mediated tumor immune e...

Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.

PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagn...

Robotic calvarial bone sampling.

The aim of this study was to assess the feasibility of complex unicortical calvarial harvesting by u...

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.

Many therapies in clinical trials are based on single drug-single target relationships. To further e...

A synthetic data generation system for myalgic encephalomyelitis/chronic fatigue syndrome questionnaires.

Artificial intelligence or machine-learning-based models have proven useful for better understanding...

[Artificial Intelligence for computer-aided leukemia diagnostics].

The manual examination of blood and bone marrow specimens for leukemia patients is time-consuming an...

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of ...

A deep learning-based interpretable decision tool for predicting high risk of chemotherapy-induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy.

OBJECTIVE: This study aims to develop a risk prediction model for chemotherapy-induced nausea and vo...

Machine Learning for Risk Prediction: Does One Size Really Fit All?