On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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6 results for “Adenocarcinoma”

An Amalgamation of Classical and Quantum Machine Learning For the Classification of Adenocarcinoma and Squamous Cell Carcinoma Patientsstat.ML

Quantum machine learning classifies lung cancer subtypes.

problem Accurately classify Adenocarcinoma vs Squamous cell carcinoma patients.

method Amalgamation of classical and quantum machine learning models, feature selection, QCrush data representation, Quantum Boltzmann Machine.

result Successfully classified 104 non-small cell lung cancer patients.

Quantum machine learning Cancer classification Adenocarcinoma Squamous cell carcinoma Gene expression

2018-10-29abs ↗pdf ↗

Horseshoe Forests for High-Dimensional Causal Survival Analysisstat.ME

Bayesian tree ensemble model for estimating treatment effects in high-dimensional survival data.

problem Estimating heterogeneous treatment effects in censored survival data with many covariates.

method Developed a Bayesian tree ensemble model with a horseshoe prior for adaptive shrinkage.

result Accurately estimates treatment effects in high-dimensional covariate spaces and non-linear functions.

Bayesian tree ensemble horseshoe prior survival analysis treatment effects high-dimensional data

2025-07-29abs ↗pdf ↗

Mahalanonbis Distance Informed by Clusteringstat.ML

A fundamental question in data analysis, machine learning and signal processing is how to compare between data points. The choice of the distance metric is specifically challenging for high-dimensional data sets, where the problem of meaningfulness is more prominent (e.g. the Euclidean distance between images). In this…

2017-08-13abs ↗pdf ↗

Learning Permutation Invariant Representations using Memory Networkscs.LG

MEM learns set functions from permutation-invariant data.

problem Learning from sets of instances with labels only on sets, not instances.

method Memory-based Exchangeable Model (MEM) with self-attention mechanism.

result Achieved 84.84% accuracy on lung cancer classification.

Memory Networks Set Functions Permutation Invariance Neural Networks Lung Cancer Classification

2019-11-18abs ↗pdf ↗

INN: Inflated Neural Networks for IPMN Diagnosiscs.CV

Inflated neural networks improve IPMN diagnosis from MRI scans.

problem Challenges in diagnosing IPMN from limited annotated data and 3D volumetric MRI.

method Developed two novel inflated deep network architectures, InceptINN and DenseINN, trained on ImageNet.

result Absolute improvement of 8.76% in accuracy for diagnosing IPMN.

IPMN diagnosis Inflated neural networks Multisequence MRI Deep learning Pancreatic cancer

2019-06-30abs ↗pdf ↗

Supervised topological data analysis for MALDI mass spectrometry imaging applicationsstat.ML

New framework distinguishes lung cancer subtypes using MALDI mass spectrometry.

problem Distinguishing between adenocarcinoma and squamous cell carcinoma subtypes in lung cancer.

method Supervised topological data analysis on MALDI mass spectrometry imaging data.

result The proposed framework successfully classifies lung cancer subtypes with competitive results.

lung cancer MALDI MSI topological data analysis subtyping logistic regression

2023-02-27abs ↗pdf ↗