Wip
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Ideas ¶
Planned (17) ¶
- Abstract Intent Machines intent machine, user intentions, automation, machine learning
- Anoma Level
- Anoma Network Architecture networking machine, peer-to-peer networks, network security, communication protocols
- Anoma State Architecture State Machine, Storage, Execution, Resource Machine
- Comparing Two Hash Functions for Multi-Party Computation and Zero-Knowledge Hydra, Poseidon, MPC, ZKP
- Compiling Juvix to Cairo Assembly Cairo, Starknet, Anoma, Juvix, Compilers, Zero-knowledge Proofs, Functional programming
- Compiling to ZKVMs zero-knowledge proofs, zkVM, virtual machines, privacy-preserving computation
- Cross-Chain Integrity with Controller Labels and Endorsement controllers, distributed systems, network management, system architecture
- Heterogeneous Narwhal and Paxos heterogeneous protocols, typhon, interoperability, protocol integration, consensus, cross-chain, heterogeneous trust
- Heterogeneous Paxos 2.0: the Specs Heterogeneous Paxos, distributed algorithm, consensus, Learner Graph
- Intent Machines intent machine, user intentions, automation, machine learning
- Intent-centric Applications for the Anoma Resource Machine Anoma Resource Machine, Resource Model, Anoma Applications
- Message Logic Distributed Systems, Dynamic Modal Logic, Service Commitments
- Multichat
- Ordering Machine ordering machine, transaction ordering, consensus algorithms, distributed ledgers
- Public Signal
- State Architecture
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Description: This project will create simple metrics from the company's data to identify potential fraud indicators. These metrics will include:
High frequency of reimbursement slips by the same customer over short periods. Issuance of medical licenses by the same doctor for patients within the same family or company. Treatments performed by doctors without proper credentials or the right skill set/competence. Track record for foreign doctors, including treatments provided or licenses issued.
New Metrics to be developed include:
Reimbursement Frequency Score: This score tracks how often a customer submits claims in a short period, flagging those with unusually high frequencies. Doctor Issuance Metric: This metric monitors how often the same doctor issues medical licenses to related individuals (the same family or company), looking for suspicious patterns. Unqualified Treatment Indicator: This metric flags treatments performed by doctors without proper certification or degrees. Doctor Nationality Consistency Metric: Detects mismatches between the doctor's nationality and treatments that are typically associated with other national medical practices.