Stem Cell Research

Predictors of residual tricuspid regurgitation after interventional therapy: an automated deep-learning CT analysis.

Computed tomography (CT) is used as a valuable tool for device selection for interventional therapy in tricuspid regurgitation (TR). We aimed to evaluate predictors of TR reduction using CT and automated deep learning algorithms. Patients with severe to torrential TR and CTs prior to either percutaneous annuloplasty (PA) or tricuspid transcatheter edge-to-edge repair (T-TEER) were enrolled. CTs we...

Publication Ethics in the Era of Artificial Intelligence.

The application of new technologies, such as artificial intelligence (AI), to science affects the way and methodology in which research is conducted. While the responsible use of AI brings many innovations and benefits to science and humanity, its unethical use poses a serious threat to scientific integrity and literature. Even in the absence of malicious use, the Chatbot output itself, as a softw...

Advancing aneurysm management: the potential of AI and machine learning in enhancing safety and predictive accuracy.

Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscores the need for effective treatment and early dete...

Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired rena...

Feasibility of Adjunct Therapy with a Robotic Hand Orthosis after Botulinum Toxin Injections in Persons with Spasticity: A Pilot Study.

Upper-limb spasticity, frequent after central nervous system lesions, is typically treated with botulinum neurotoxin type A (BoNT-A) injections to red...

Assessing the use of the novel tool Claude 3 in comparison to ChatGPT 4.0 as an artificial intelligence tool in the diagnosis and therapy of primary head and neck cancer cases.

Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary tumor board approach for individual treatment ...

Robotic-Enhanced Prosthetic Liners for Vibration Therapy: Reducing Phantom Limb Pain in Transfemoral Amputees.

Phantom limb pain, a common challenge for amputees, lacks effective treatment options. Vibration therapy is a promising non-pharmacologic intervention...

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pat...

Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. Wh...

Combining Metabolomics and Machine Learning to Identify Diagnostic and Prognostic Biomarkers in Patients with Non-Small Cell Lung Cancer Pre- and Post-Radiation Therapy.

Lung cancer is the leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) accounting for over 85% of cases and poor ...

Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms.

INTRODUCTION: In 2021, the International Diabetes Federation reported that 537 million people worldwide are living with diabetes. While glucagon-like ...

A self-supervised embedding of cell migration features for behavior discovery over cell populations.

BACKGROUND AND OBJECTIVE: Recent studies point out that the dynamics and interaction of cell populations within their environment are related to sever...

Deep learning-based voxel sampling for particle therapy treatment planning.

Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially...

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

BACKGROUND: Lenvatinib plus PD-1 inhibitors and interventional (LPI) therapy have demonstrated promising treatment effects in unresectable hepatocellu...

Neurological insights into brain-targeted cancer therapy and bioinspired microrobots.

Cancer, a multifaceted and pernicious disease, continuously challenges medicine, requiring innovative treatments. Brain cancers pose unique and daunti...

Novel AT2 Cell Subpopulations and Diagnostic Biomarkers in IPF: Integrating Machine Learning with Single-Cell Analysis.

Idiopathic pulmonary fibrosis (IPF) is a long-term condition with an unidentified cause, and currently there are no specific treatment options availab...

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy.

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological si...

Proton spot dose estimation based on positron activity distributions with neural network.

BACKGROUND: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in ...

A deep learning-driven discovery of berberine derivatives as novel antibacterial against multidrug-resistant Helicobacter pylori.

Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high preva...

The ethics of artificial intelligence systems in healthcare and medicine: from a local to a global perspective, and back.

Artificial intelligence systems (ai-systems) (e.g. machine learning, generative artificial intelligence), in healthcare and medicine, have been receiv...