Ethosoft

Ethosoft Works

Problems explored in practice.

Projects, prototypes, competition systems, and open research releases—kept separate from our scholarly papers and described at the maturity level supported by their project records.

14 project records 2 open research releases 4 focus areas

How to read this archive

Evidence before claims.

These records were reconstructed from the project briefs, reports, presentations, and technical notes in Ethosoft's working archive. “Reported result” means a value documented in those materials; it does not imply independent reproduction, peer review, regulatory clearance, or clinical validation.

Healthcare

Signals, images, and molecular structure.

Exploratory decision-support systems. None of the records below should be interpreted as a medical device or diagnostic service.

Research prototypeEEG · Edge AI

Epilepsy Early-Warning System

A wearable-to-edge concept for distinguishing ictal, preictal, postictal, and normal EEG states and exploring whether a useful warning can be produced before a seizure.

Data and signals
TUH EEG records, reduced to an eight-channel configuration.
Pipeline
Multi-scale temporal features, channel attention and fusion, temporal context modeling, OpenBCI Cyton, Raspberry Pi, and a Flutter companion app.
Intended workflow
Wearable sensing, edge inference, alerts, emergency location sharing, and medication tracking.

Evidence boundary: the local brief sets a two-to-five-minute pre-seizure warning as a design target; it does not provide prospective clinical validation for that target.

Competition projectChest X-ray · Explainability

Explainable Cardiomegaly Screening

A frontal chest X-ray system that combines anatomical segmentation, cardiothoracic measurements, CNN evidence, and tabular classification instead of relying on a single opaque score.

Data
Project materials describe PadChest, MIMIC-CXR, CheXpert, VinDr-CXR, NIH ChestX-ray14, and CheXmask-derived masks.
Models
U-Net++ for the heart, DeepLabV3+ with ResNet101 for the lungs, and LightGBM over CTR, area features, and CNN probability.
Reported results
Heart IoU 87.26%; right/left lung IoU 91.11%/89.53%; classifier F1 91.4%; CTR SMAPE 7.5%.

Interpretability: the report includes cardiothoracic ratio, heart/lung area features, Grad-CAM, and SHAP. It also documents StyleGAN2-ADA synthetic-data experiments.

Competition projectColonoscopy · Segmentation

Colonoscopy Polyp Segmentation

A multi-dataset study of polyp masks in colonoscopy frames, built around reproducible preprocessing and comparative segmentation experiments.

Models explored
Attention U-Net, U-Net++, DeepLabV3+, PVT-Cascade, and SSFormer-S with a progressive refinement network.
Ablations
Learning-rate comparisons, bilateral filtering, elastic deformation, image generators, and cosine-annealing warm restarts.
Reported results
The report records U-Net++ validation mean IoU of 0.8907 and PolypDB mean IoU of 0.8655, alongside uneven results across external datasets.

Generalization note: the documented cross-dataset variance is retained because aggregate validation performance alone can hide distribution shift.

Research conceptEchocardiography · Video

Ultrasound Heart-Failure Assessment

An echocardiography-video concept for segmenting the left ventricle, estimating end-diastolic and end-systolic volumes, and deriving ejection fraction.

Visual model
Multi-scale feature extraction with spatial attention and feature fusion.
Temporal model
Motion analysis across the cardiac cycle rather than isolated-frame classification.
Planned output
An EF estimate and low-versus-preserved EF decision-support category.

Evidence boundary: the available brief describes the architecture and intended outputs but contains no evaluation cohort or validated performance result.

Computational studyBioinformatics · Docking

Protein Mutation Modeling and G6PD Screening

Two linked computational workstreams: multimodal mutation analysis over sequence and structure, followed by a focused study of how the R166H variant changes G6PD structure and small-molecule binding profiles.

Mutation models
NCBI cDNA and protein data, AlphaFold structures, a GNN, sequence-based XGBoost/ensemble models, and a combined multimodal model. The brief reports F1 scores of 72%, 84%, and 94% respectively.
G6PD case study
Wild-type and R166H G6PD sequences modeled with AlphaFold and compared at the structural level.
Screen
More than 8,000 DrugCentral compounds were filtered with RDKit; 3,799 molecules were docked against both forms with GNINA.
Analysis
Binding energies, mutant-versus-wild-type ΔΔG, CNN pose scores, distributions, and top-ligand comparisons.

Evidence boundary: the F1 values are project-reported and the docking results are computational hypotheses. Neither establishes a therapy or proves restoration of protein function without independent and laboratory validation.

Exploratory studyGCK · Variant classification

MODY2 Variant Classification

A small-data experiment classifying GCK variants associated with MODY2 from local sequence context.

Dataset
317 pathogenic and 39 benign variants assembled from ClinVar and LOVD.
Method
3-mer encoding, SMOTE within the training workflow, a 20% held test split, and a voting ensemble spanning tree, linear, kernel, and boosting models.
Reported results
Accuracy 78.35%, ROC AUC 0.7987, and PR AUC 0.8313.

Evidence boundary: 356 labeled variants are not sufficient for a clinical claim; the result is presented as an exploratory baseline.

Prototype conceptFundus · OCT

Fundus and OCT Eye Analysis

A multimodal ophthalmic-imaging concept for disease classification and lesion localization across fundus photographs and OCT scans.

Scope
The brief targets more than 25 eye conditions across the two modalities.
Preprocessing
Contrast adjustment, Gaussian smoothing, and histogram equalization.
Model direction
CNNs, attention, transfer learning, and a prototype Gemini-connected interpretation layer.

Evidence boundary: accuracy, F1, and IoU are proposed evaluation metrics; the available document does not report a completed validation study.

Prototype conceptHeart sounds · Signal processing

AI Digital Stethoscope

A digital-auscultation workflow for cleaning heart sounds, extracting acoustic features, and supporting normal-versus-murmur screening.

Features
MFCC, RMS energy, zero-crossing rate, and normalized temporal representations.
Models considered
Temporal CNN/RNN approaches and classical SVM or random-forest baselines.
Interface
Mobile or web software paired with a Bluetooth-capable digital stethoscope.

Evidence boundary: the project file contains a system design but no reported patient-level evaluation.

Early conceptEMG · Neuromuscular

Neuropathy and Myopathy EMG Analysis

An early research direction for using electromyography signals to distinguish neuropathic and myopathic patterns.

Available scope
The local archive currently contains only the problem statement.
Required next evidence
A defined dataset, patient-level split, signal preprocessing protocol, baseline models, error analysis, and clinical evaluation plan.

Status: listed for completeness as an early concept; no implementation or result is claimed.

Education & products

Tools designed around people.

Product-oriented concepts that connect machine learning with assessment, planning, mobility, and online safety.

Product prototypeMobility · Optimization

Traffic-Aware Eco-Routing

A mobile route planner that optimizes for predicted fuel use rather than distance or travel time alone.

Inputs
Road topology, live traffic, road characteristics, and vehicle parameters from mapping services and OpenStreetMap-compatible data.
Methods
A* and Dijkstra search informed by a Gaussian-mixture-regression fuel model.
Delivery
A Flutter application intended for Android and iOS.

Evidence boundary: the brief describes favorable fuel-use trials without a reproducible benchmark table; no numeric saving is claimed here.

Product prototypeEducation · Assessment

AI English Exam Evaluation

A teacher-configurable system for scoring and explaining performance across writing, listening, reading, and speaking tasks.

Input
Typed answers, photographed written papers, audio, and generated listening/reading material.
Assessment
Teacher-defined rubrics with model-assisted scoring and personalized feedback.
Prototype stack
Gemini 2.5 Flash with planned mobile and web delivery.

Responsible-use requirement: reliability should be measured against multiple human raters before scores are used for consequential assessment.

Product prototypeYKS · Personal planning

Studium AI Study Coach

A cross-platform YKS companion combining study planning, practice analysis, motivation, focus sessions, guidance content, and university-choice tools.

Core experience
Personal plans, Pomodoro sessions, exam analytics, score calculation, resource tracking, and preference guidance.
Stack
Flutter targets Android, web, and Windows; the project brief names Gemini 2.5 Pro for assistant features.
Product direction
An open-source, unified alternative to fragmented study utilities.

Status: the archive describes the intended feature set and roadmap, not validated learning outcomes.

Safety conceptNLP · Online wellbeing

Context-Aware Cyberbullying Protection

A multilingual moderation concept that considers conversation context before blocking or escalating potentially harmful messages.

Interventions
Message blocking, warnings, account escalation, platform reporting, and educational prompts.
Safeguards proposed
Parent alerts for younger users, limited recent-message review, sentiment analysis, and a feedback loop.
Research need
Age-appropriate consent, privacy minimization, appeal mechanisms, multilingual bias testing, and false-positive analysis.

Status: the available material is a product and policy concept; no deployed moderation system or benchmark result is claimed.

Computational research

Learning from high-energy events.

A research design connecting simulated and observed collider events with interpretable signal-versus-background classification.

Research conceptCERN · High-energy physics

Machine Learning for Collider Events

A proposed analysis of LHC proton-collision events for separating Standard Model backgrounds from rare signatures associated with Higgs processes or dark-matter searches.

Data
Open CERN/LHC collision records paired with Monte Carlo simulation.
Signals
Missing transverse energy, mono-jet, and mono-X topologies against QCD and other backgrounds.
Evaluation
Classifier quality should be paired with systematic uncertainties and physics significance, not accuracy alone.

Evidence boundary: the file defines the scientific problem and evaluation direction but does not contain an executed analysis or result.

Open research releases

Code and artifacts you can inspect.

These detail pages keep their original permanent URLs while being organized under the Works archive.

Open model releaseLoRA · PEFT · GGUF

Qwen3-1.7B ResearchReasoning JSON RL

A compact adapter for evidence-grounded research QA, source selection, claim verification, uncertainty reporting, and strict JSON generation.

View the model record
Open experimentKV cache · Exact recall

Risk-Routed Heterogeneous KV Memory

An inference-time investigation of routing exact-critical context to full precision while lower-risk context uses quantized KV representations.

View the experiment record