Hematology

Leukemia

Latest AI and machine learning research in leukemia for healthcare professionals.

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Showing 190-210 of 7,897 articles
Artificial intelligence-based muscle analysis risk assessment of treatment-related toxicity in metastatic colorectal cancer.

IntroductionUp to 60% of adults with metastatic colorectal cancer (mCRC) receiving combination cytot...

An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.

The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful l...

Evaluation of Artificial Intelligence Models for Nutritional Symptom Management in Breast Cancer Patients Undergoing Chemotherapy.

The purpose of the study is to determine if artificial intelligence (AI) models could provide dietar...

Machine learning-based optimization of cytotoxicity testing for assessing Zn-based biodegradable metals.

Zinc (Zn)-based biodegradable metals are emerging as promising candidates for biomedical implants. N...

Machine learning approach to single cell transcriptomic analysis of Sjogren's disease reveals altered activation states of B and T lymphocytes.

Sjogren's Disease (SjD) is an autoimmune disorder characterized by salivary and lacrimal gland dysfu...

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients o...

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics.

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparallel...

Organoid-Guided Precision Medicine: From Bench to Bedside.

Organoid technology, as an emerging field within biotechnology, has demonstrated transformative pote...

Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.

BACKGROUND AND OBJECTIVE: This study has two main objectives. First, to evaluate a feature selection...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patie...

Implementing large language model and retrieval augmented generation to extract geographic locations of illicit transnational kidney trade.

BACKGROUND: Illicit kidney trade networks, operating globally, involve intricate interactions among ...

All-Electrical Control of Spin Synapses for Neuromorphic Computing: Bridging Multi-State Memory with Quantization for Efficient Neural Networks.

The development of energy-efficient, brain-inspired neuromorphic computing demands advanced memory d...

Risk prediction model for chemotherapy-induced nausea and vomiting in cancer patients: a systematic review.

BACKGROUND: Chemotherapy-induced nausea and vomiting increase the healthcare burden and lead to adve...

OrgaMeas: A pipeline that integrates all the processes of organelle image analysis.

Although image analysis has emerged as a key technology in the study of organelle dynamics, the comm...

Learning Chemotherapy Drug Action via Universal Physics-Informed Neural Networks.

OBJECTIVE: Quantitative systems pharmacology (QSP) is widely used to assess drug effects and toxicit...

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