Models for Diagnosing Covid Diagnosis

Was wondering if validated ML models existed, had not heard of any.  What is missing?   The article suggests lack of data, can that be?    Yes, if the needed validated supporting metadata was not gathered systematically.   Passed this piece on to some people with clinical diagnosis experience. 

ML Models for Diagnosing Covid-19 Not Yet Suitable for Clinical Use

University of Cambridge (U.K.),  March 15, 2021

A review of studies containing descriptions of machine learning (ML) models for diagnosing Covid-19 by researchers at the U.K.'s University of Cambridge concluded that none are yet suitable for detecting or diagnosing the virus from standard medical imaging. The team ultimately reviewed 62 studies, and invalidated each model's suitability due to biases in study design, methodological flaws, lack of reproducibility, and publicly available "Frankenstein datasets." Many ML models were trained on sample datasets that were too small to be effective, failed to specify their data's origins, were trained and tested on the same data, or lacked involvement from radiologists and clinicians. Cambridge's James Rudd said, "These early studies show promise, but they suffer from a high prevalence of deficiencies in methodology and reporting, with none of the literature we reviewed reaching the threshold of robustness and reproducibility essential to support use in clinical practice."

AI and Clinical Trials

General overview of the state of the technical advances.

Artificial Intelligence Ushers in a New Era of Cost-Effective Clinical Trials 
Contributed Commentary by James Streeter, Global Vice President Life Sciences Product Strategy, Oracle Health Sciences 

Clinical trials have changed significantly over the past several years. As drugs and devices—and the conditions they are trying to impact—have become increasingly more complex, so has the design and structure of clinical trials. But protocols are costly to change and identifying and enrolling the right patient cohorts is also no easy feat—especially when rare diseases are the target. So, how are study teams keeping up with this rapid pace of change?  

Pharmaceutical companies, biotechs, and CROs have been incorporating technology at various stages of the trial process to address these challenges; but, ironically, some of these technologies have introduced new challenges such as the sheer volume of data that are being generated.   ... "  ... ' 

Clinical Trials Bot

A new direction I have not heard as yet.  Underlying architecture would be interesting. Data being gathered to construct elements of the trial?

Microsoft Built a Bot to Match Patients to Clinical Trials  By Dina Bass in Bloomberg

A chat bot that began as a hackathon project at Microsoft Corp.'s lab in Israel makes it easier for sick patients to find clinical trials that could provide otherwise unavailable medicines and therapies.

The Clinical Trials Bot lets patients and doctors search for studies related to a disease and then answer a succession of text questions. The bot then suggests links to trials that best match the patients’ needs. Drugmakers can also use it to find test subjects  .... " 

Strategy for Storing Clinical Trial Data with Blockchains

Here the goal example for using Blockchains  is the integrity of stored results among multiple parties.  Assuming some parties have an incentive to tamper with the data.   So why not use a database ledger with assured strong passwords and encryption?   

The argument being made is that the blockchain cannot be altered without leaving evidence of tampering, using a combination of hashing and proof-of-work strategies. Yet there have been a number of cases lately where the blockchain was not as strong as theoretically expected.   Due to some bad design and operational choices. 

The approach below uses centralized authority to enforce choices, similar to enforcing better passwords in computer systems.   Since hashing is used, the choice of random numbers to create the hash is key, and we assume the central authority enforces that.

Researchers Create Method to Ensure Integrity of Clinical Trials Data With Blockchain
News-Medical.net
By James Ives

University of California, San Francisco (UCSF) researchers have developed a proof-of-concept method for ensuring the integrity of clinical trials data, using blockchain. The prototype system produces an inflexible audit trail in which tampering can be easily flagged. The system is designed to run through a Web portal, so every time new data is entered on a given trial participant, the sender, receiver, timestamp, and file attachment containing the data, as well as the hash of the previous block of data relating to the patient, are recorded onto a new block with its own unique signature. A regulator with centralized authority must operate the portal, register all parties, and maintain a ledger of the blockchain's hashes. Real-time reporting of data to the regulator could augment the safety and effectiveness of clinical trials. Said UCSF's Atul Butte, "We think it could someday be useful for pharma companies running clinical trials."  .... "