Monthly Archives: September 2014

Voice Recognition 3.0

Can we just pass right over voice recognition 2.0? I am getting really tired and bored after 25+ years of incrementalism. For sure, the incrementalism has paid off – just look at cars and iPhones and siri and a host of call center applications (which are equally annoying and progressive).

So here is my version of voice recognition 3.0. It would have these characteristics:

Goodbye Typing: it is so good that typing basically becomes a secondary application. Most emails and text messages etc would be generated by voice not be typing.
Grammar, stutter, and uh checks: it is so good that it comes to recognize uh’s and simple makes sure that I want to delete them and then does so automatically. Ditto bad grammar.
Personal vocabularies – it is so good that it builds a personal vocabulary for me over time and remembers it. For example, why can’t I expect my voice recognition system to learn that I live in Serenbe? And will use it in my communications a lot? Why does the best system today choke and think I am saying “Saran Be” or “Seren Bee”. But that is easy. Tough is that it should know that my brother lives in West Townsend, and that the movie I saw last Saturday was called The Hunger Games (and all I should need to say is “the movie I saw last Saturday night” or “the people I met at lunch today” – in other words it should draw regularly and liberally from my calendar and emails as I allow it to do so).
Search: I am tired of talking about this one. We should be able to search using natural language – just buy saying what is on my mind. “I vaguely recall a great article in one of the national magazines, I guess it was published in the last 24 months, and it spoke about genomic mapping getting cheaper and better. Can you find me that article?

Edison Electric: latest # on Smart Meters

50 million out there and growing fast:
Edison Report on Smart Meters

The graph below shows progress over time. Doubled from 2009 to 2011. Doubled again from 2011 to 2014!



But still very few experiments with price signals. Some interesting ones though, all voluntary.

Interesting that there is no political consensus that there should be peak demand prices that are MUCH higher than average time of day. Conversely, it is pretty amazing that no movement has surfaced to create a uber-cheap energy pricing time of day – probably from midnight to 5 a.m. If such a movement were to develop, I would argue that pricing at $5/KWH or less would be totally appropriate for off-hours, $10 for regular, and $50 or more for the 30 minutes around “peak” would be very appropriate. This would create the right incentives and effectively stop the idiotic construction of electric utilities in the US. After all, these incremental facilities have one and only one objective – to cover peak demand, which is still unfortunately growing.

Commentary pulled out below:

Smart pricing programs include Baltimore Gas & Electric’s Smart Energy Rewards, Oklahoma Gas & Electric’s SmartHours, Pepco and Delmarva Power’s Peak Energy Savings Credit, San Diego Gas & Electric’s Reduce Your Use, and Southern California Edison’s Save Power Day.
Some customers are using devices like programmable controllable thermostats to respond to the price signals, while others are altering their behavior – all to take advantage of the opportunity to save money on their electricity bill. While these programs have different names and nuances, all are enabled by smart meters and, for most customers, the result is energy savings, bill savings, and increased satisfaction.

My own check of the data tells me that there are about 50 big utilities, and – with the exception of some really slow ones, like NY and Illinois and Dominion in Virginia, and also NC – most are either full deployed or will be by end of 2015.

On the other hand, pricing strategies area, well, pathetic. Not sure why. Here is my spreadsheet:

EEI Smart Meter Status_201409

Weather: Big Data&Big Forecast Progress

Weather Channel Article

Behind the Scenes: How We Make Billions of Forecasts 96 Times a Day

David Kenny
Chairman & CEO at The Weather Company

In the past several months, we have improved the accuracy of precipitation forecasts by another 15% and the accuracy of temperature forecasts by 2 degrees Fahrenheit. This is entirely because we are now forecasting for every location on Earth (at least 3 billion named locations) instead of mapping people to the approximately 2MM locations where forecasts have traditionally been done.

….mobile access is always current. So this means that our current day forecasts are now updated 96 times per day, and days 2-15 are updated at least 24 times per day.

….Our new forecasting platform is the largest application in the Amazon Web Services cloud. We are currently scaled to deliver 115,000 unique forecasts per second, or more than 10 Billion forecasts per day.

….We are voracious consumers of data to make this happen. We build on the incredibly skillful global models of government agencies, such as NOAA and ECMWF, as well as models built by some of the world’s great universities and research organizations. We add the data we collect from airplanes (who provide that data as part of our aviation weather service contracts with most airlines and private operators.) We also work with tens of thousands of individuals who buy and build personal weather stations, connect those stations to our Weather Underground network and send us their own weather data every 2.5 seconds. And we are exploring new potential observations from home sensors, windshield wipers, smartphone air pressure gages, and literally billions of additional sources that can sustain this faster rate of innovation and improved forecasting skill.

….Two years ago, we began creating this new forecasting system. The bulk of the work was building the statistical optimization to calibrate and blend the world’s best global weather models. And then we supported these algorithms with more and faster computing power, as well as more observations, to enable constant machine learning. At the same time, machine learning and algorithmic forecasts sometimes miss enough color for people to truly know what the forecast means, and how to act. So we invented an exception process when our human meteorologists and social scientists need to interpret and verbalize certain forecasts, especially when life and property-threatening storm systems are predicted.

Weather Channel Dashboard

Cardiologists and Wearables

Mark Bard writes:

Your Cardiologist Does Not Want Your Wearable Data – Addressing the Concerns of Physicians As We Enter the “Connected Health” Era

Last week we discussed the current and future market opportunity for patients with heart disease to utilize health and fitness trackers. Only 12% of cardiovascular/heart disease patients are using trackers – and only 6% more report they are interested in using them in the future. However, understanding the patient side of the question is only one side of the equation. For connected health (and wearables) to drive the most value we really need the cardiologists/physician to be part of the equation through utilization of the data in care and treatment planning or by providing positive reinforcement to patients using the technology.

Recent data from Digital Insights Group show approximately 1 in 4 cardiologists currently have patients sharing data from fitness and activity trackers (such as Fitbit) with them in their practice. This number is higher than the number of patients using a device because it reflects the population of physicians with any patients using a device to share data with them in their practice.

Beyond the current population of cardiologists utilizing patient generated activity and fitness data, future interest (based on current devices and data streams) remains limited at the current time. In an effort to better understand what is holding back all those physicians we explored some of the barriers to making the move – or using data from patients attempting to share the data with their physician today.

The number one objection among cardiologists today is … Fear of Data Overload. Just over half of cardiologists agree the potential stream of user-generated health and activity data may be too much to assimilate, integrate, and utilize with regard to making treatment decisions. This underlines the importance of tools and dashboards to help physicians (and their team) better understand the trends, outliers, and how to quickly and efficiently integrate the data into their existing medical records platforms.

The next one (and perhaps understated given we don’t have a lot of examples in this space yet) is the liability of receiving this data from patients. In other words, imagine the deposition lawyer asking a cardiologist about when his practice received data showing the patient was clearly engaged in physical activity that placed them at risk given their recent diagnosis and proposed treatment plan. Yes, we’ll eventually be able to limit the scope and place the responsibility back with the patient … but until that time cardiologists (and physicians overall) will be cautious to blindly accept user-generated data.

Finally, one that will take time to address is the concern that the data generated from various devices lacks any sense of “data standards” that can be used to plan care for specific patients. In other words, will one or two platforms became the “gold standard” for key cardiovascular and heart related metrics generated by these platforms? Have those metrics been verified in clinical trials (or any trials) to show a correlation to health, wellness, treatment, and outcomes?

The transition to connected health has already begun and the latest push from Apple and Google should help move the industry forward. However, engaging the physician and addressing their key concerns (data overload, liability, standards) will be critical to making the transition effective for both the patient and their physician.

US Preventive Services Task Force

About the Task Force

U.S. Preventive Services Task Force

Recommendations for Adults

The U.S. Preventive Services Task Force (USPSTF) was convened by the Public Health Service to rigorously evaluate clinical research in order to assess the merits of preventive measures, including screening tests, counseling, immunizations, and preventive medications.

Clinical Categories
Heart and Vascular Diseases
Injury and Violence
Infectious Diseases
Mental Health Conditions and Substance Abuse
Metabolic, Nutritional, and Endocrine Conditions
Musculoskeletal Disorders
Obstetric and Gynecologic Conditions
Vision and Hearing Disorders

USPSTF Recommendations for Children and Adolescents

Aspirin/NSAIDs for Prevention of Colorectal Cancer Preventive Medication (2007)
Bladder Cancer: Screening (2011)
Breast and Ovarian Cancer, BRCA Testing: Screening (2013)
Breast Cancer: Screening (2009)
Breast Cancer Preventive Medication (2013)
Cervical Cancer: Screening (2012)
Colorectal Cancer: Screening (2008)
Gynecologic Cancers: Counseling (Inactive)
Lung Cancer: Screening (2013)
Oral Cancer: Screening (2013)
Ovarian Cancer: Screening (2013)
Pancreatic Cancer: Screening (2004)
Prostate Cancer: Screening (2012)
Skin Cancer: Screening (2009)
Skin Cancer: Counseling (2012)
Testicular Cancer: Screening (2011)
Thyroid Cancer: Screening (1996); (Update in Progress)
Tobacco Cessation (Smoking): Counseling and Interventions (Adults) (2009)
Vitamin Supplementation to Prevent Cancer and Cardiovascular Disease: Preventive Medication (2014)

Heart and Vascular Diseases
Abdominal Aortic Aneurysm: Screening (2014)
Additional Risk Factors for Intermediate CHD Risk: Screening (2009)
Aspirin for Primary Prevention of Cardiovascular Disease: Preventive Medication (2009)
Blood Pressure in Adults (Hypertension): Screening (2007)
Carotid Artery Stenosis: Screening (2014)
Coronary Heart Disease (Electrocardiography): Screening (2012)
Coronary Heart Disease (Risk Assessment, Nontraditional Risk Factors): Screening (2009)
Lipid Disorders in Adults (Cholesterol Abnormalities, Dyslipidemia): Screening (2008)
Peripheral Artery Disease and Cardiovascular Risk Assessment: Screening (2013)
Tobacco Cessation (Smoking): Counseling and Interventions (Adults) (2009)
Vitamin Supplementation to Prevent Cancer and Cardiovascular Disease: Preventive Medication (2014)

Infectious Diseases
Bacteriuria: Screening (2008)
Chlamydial Infection: Screening (2007)
Gonorrhea: Screening (2005)
Hepatitis B Virus Infection in Nonpregnant Adolescents and Adults: Screening (2014
Hepatitis B Virus Infection (Pregnant Women): Screening (2009)
Hepatitis C Virus Infection: Screening (2013)
Herpes Simplex, Genital: Screening (2005)
Human Immunodeficiency Virus (HIV) Infection: Screening (2013)
Immunizations, Adult
Rubella: Immunizations (1996)
Rubella: Screening (Inactive)
Sexually Transmitted Infections: Counseling (2008)
Syphilis: Screening (2004)
Syphilis (Pregnant Women): Screening (2009)
Tuberculosis Infection: Screening (1996)

Injury and Violence
Falls Prevention in Older Adults: Counseling and Preventive Medication (2012)
Family Violence: Screening (2004)
Intimate Partner Violence and Elderly Abuse: Screening (2013)

Mental Health Conditions and Substance Abuse
Alcohol Misuse: Screening and Counseling (2013)
Cognitive Impairment (Dementia): Screening (2014)
Depression, Adult: Screening (2009)
Drug Use, Illicit: Screening (2008)
Suicide Risk in Adolescents, Adults,and Older Adults: Screening (2014)
Tobacco Cessation (Smoking): Counseling and Interventions (Adults) (2009)
Top of Page
Metabolic, Nutritional, and Endocrine Conditions
Celiac Disease: Screening (2014)
Diabetes Mellitus: Screening (2008)
Healthful Diet and Physical Activity to Prevent Cardiovascular Disease: Counseling (2012)
Healthful Diet and Physical Activity to Prevent Cardiovascular Disease in At-Risk Adults: Counseling (2014)—New!
Hemochromatosis: Screening (Inactive)
Iron Deficiency Anemia (Anemia): Screening (2006)
Menopausal Hormone Therapy: Preventive Medication (2012)
Obesity in Adults: Screening and Counseling (2012)
Thyroid Disease: Screening (2004)
Vitamin D and Calcium Supplementation to Prevent Fractures: Preventive Medication (2013)
Vitamin D Deficiency: Screening (2013)
Vitamin Supplementation to Prevent Cancer and Cardiovascular Disease: Preventive Medication (2014)

Musculoskeletal Disorders
Osteoporosis: Screening (2011)
Top of Page
Obstetric and Gynecologic Conditions
Aspirin Prophylaxis in Pregnancy (Preeclampsia): Preventive Medication (1996)
Bacterial Vaginosis in Pregnancy: Screening (2008)
Breastfeeding: Counseling (2008)
Folic Acid Supplementation: Preventive Medication (2009)
Gestational Diabetes: Screening (2014)
Preeclampsia: Screening (1996); (Update in Progress)
Rh Incompatibility: Screening (2004)
Rubella: Screening (Inactive)

Vision and Hearing Disorders
Glaucoma: Screening (2013)
Hearing Loss, Older Adults: Screening (2012)
Impaired Visual Acuity in Older Adults: Screening (2009)
Visual Acuity in Older Adults, Impaired: Screening (2009)

Chronic Obstructive Pulmonary Disease: Screening (2008)
Dental and Periodontal Disease: Counseling (Inactive)
Kidney Disease (Chronic): Screening (2012)
Sleep Apnea: Screening (2014)

Current as of August 2014
Internet Citation:
Recommendations for Adults. U.S. Preventive Services Task Force.

Well-Being Assessment 101 – LABS

The exploration here is to try to get very clear about how LABS and their associated datasets can inform the average person’s curiosity about their general well-being.

Obviously, this is a highly technical subject, and not one that I am trying to master – I just want the basics.

So any good “well-being assessment” begins with MARVELS (see JCR Post on MARVELS).

This post focuses on the “L” – LABS.

The “L” in MARVELS is for “LABS” – in this domain, there are blood, stool, urine, saliva, HAIR LABS. Specimens need to be collected and shipped per protocols that can be very stringent. Costs are incurred accordingly.

An interesting distinction is this: which tests are cellular and which are blood tests? See THIS ARTICLE FROM WOMEN’S SPORTS NUTRITION, which argues that cellular tests are better for well-being assessments while medicine addresses disease in advanced stages and therefore relies on blood, which reveals a progression that is not evident in healthy people (even though their cellular assessment might reveal important deficiencies).

Hundreds of Tests Available

Just as there are hundreds of medical tests for diagnosing disease, there are hundreds of scientific nutritional tests available to Advanced Clinical Nutrition to identify the causes of nutritional deficiencies, biochemical imbalances and organ/gland dysfunctions.

Because blood, urine and stool are the primary specimens collected and analyzed for medical diagnosis, some people may not be aware of saliva and hair testing. Advanced Clinical Nutrition utilizes all of these specimens for clinical nutrition analyses. Below, we have provided an Analogy on how saliva, urine and hair analysis differs from blood testing.

Any Fluid or Tissue Can Be Analyzed

It is important to note that any fluid or tissue of the body can provide insight into its level of malnutrition, deficiencies, imbalances and dysfunctions, and pattern of or existing disease.

Single Tests and Testing Profiles Available

There are single tests and testing profiles. For example, one of the female saliva hormone profiles for a woman in menopause, or who has had a hysterectomy, includes six individual saliva tests, the three estrogens, progesterone, testosterone and DHEA.

Note: when obtaining blood testing for medical purposes, your physician may order from 16 to 25 blood tests in their profile. At Advanced Clinical Nutrition, we order 44 different blood chemistries in our profile. Due to insurance and Medicare cut-backs and new regulations, physicians no longer order the comprehensive blood chemistry profile (44 blood tests), as they did years ago. However, we do.

In blood, 200 test protocols have been identified – see below.

See this post below at: JCR Post on Blood Testing 101
Blood Testing 101
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Here are the basics….

See this post below at: JCR Post on Blood Testing 101

LABS (blood testing, etc)
CDC Blood Test List

There are about 200 tests that require blood samples.

The basis metabolic panel is widely used.

40-50 test for allergies.
18 are useful for male related general health screening
18 are useful for female related general health screening
7 are for detecting viruses
18 are for rheumatic evaluations
7 are hormonal related – men
7 are hormonal related – female

Some labs group the tests. An example is:
Blood test types and panels

LABS revolution
LABS By Disease
Quantified Self Movement”>Austin Example of LABS
Note this example underlines that stool, urine, saliva, and blood are all specimens.

This entry was posted in Uncategorized, Well-Being, Well-Being – PersonaL and tagged LABS on February 1, 2009. Edit