Potential Problems with Experiments
Selection Bias
Results may not be generalizable.
Experiments and control conditions may have different types of subjects.
-Randomly assign subjects to the groups.
Not always reduced to one variable
-Confounded variab
After Exam 3
-Sleep and Dream
-Sleep
*Sleep follows a daily rhythm
Biological Rhythm: Periodic fluctuations in psychological functions.
o Four Kinds in Humans
1. 90 min
a. alertness, daydreaming
2. 24 hour cycle
a. sleep, body temperature
3. 28 day cycle
importance of v to u (i.e., w(u, v) is significant. Aggregation: Finally,
given a set of normalized symptom graphs G1, G2, . . . , GK, we can also
easily combine them into an aggregated symptom graph G by averaging
the symptom matrices: G = 1 K X i Gi. Si
extracting and analyzing symptoms in longitudinal clinical notes.
SympGraph constructs symptom graphs based on colocation relations
among detected symptom mentions. Within the general formulation of
symptom graphs, we present the important clinical mining
of disability and reduces demyelinating lesions. Aspirin toxicity causes
symptoms of nausea, vomiting, headache, confusion and tinnitus or
hearing difficulties. Major side effects of carbimazole are:
agranulocytosis, thrombocytopaenia, acute hepatic necro
2000. JAMA: the journal of the American Medical Association. 2004
Mar 10;291(10):123845. 3. Kleiman EM, Liu RT. Social support as a
protective factor in suicide: Findings from two nationally representative
samples. Journal of affective disorders. Elsevier
Bartlett N, Elhadad N, Wood F. Hierarchically Supervised Latent Dirichlet
Allocation. Proceedings of the Neural Information Processing Systems
Conference (NIPS). 2011;19. 14. Halpern Y, Horng S, Nathanson LA,
Shapiro NI. A Comparison of Dimensionality Red
(dilated pupils) and agitation. Physostigmine, a reversible inhibitor of
acteylcholinesterase, is effective in treating anticholinergic symptoms
but there is a significant risk of cardiac toxicity (bradycardia, AV
conduction defects and asystole) with the
age, race, sex, socio-economic status, geographic, etc. Important public
health information can be obtained this way which may be useful in
determining how to allocate health care resources. However such data
are generally not very useful in determining c
as relief of pain or reduction of blood pressure. For instance, if 5
milligrams of drug A relieves pain as effectively as 10 milligrams of drug
B, drug A is twice as potent as drug B. Efficacy refers to the potential
maximum therapeutic response that a dr
of the loop of Henle, agents that act at this site produce a diuretic effect
much greater than that seen with other diuretic groups. Insulin glargine
is a long-acting insulin analogue, there is a smooth, prolonged
absorption profile with no peaks. As such
Tsuruoka Y, Tateishi Y, Kim J, Ohta T. Developing a Robust Part-of-Speech
Tagger for Biomedical Text. Lecture Notes in Computer Science. 2005.
pp. 38292. 19. Blei DM. Latent Dirichlet Allocation in C. Available from:
http:/www.cs.princeton.edu/~blei/lda-c
MRCPASS NOTES 4 Mesalazine can cause neutropenia. It works in IBD
by release in the terminal ileum. Mesalazine is given in the acute attacks
in Crohn's disease. Sulfasalazine (sulphapyridine and 5-amino-salicylic
acid) is used in rheumatoid arthritis. Pen
patterns extracted from similar patients like p. Finally, at the population
level, symptom expansion enables understanding of typical symptoms
to a disease. Typical symptoms as described in medical books such as
Framingham symptoms for CHF are just a smal
graph G. In addition to the immediately co-occurring symptoms, we also
perform the expansion recursively through random walk with restart
[20]. Intuitively, random walk with restart (RWR) can be regarded as
modeling a random particle that with probability
1 about extending Framingham criteria for CHF diagnosis). To facilitate
the discussion, we define the following notations: Let ES be the set of
the existing symptoms that one constructed (e.g., symptoms included in
the Framingham criteria). Let vector e R
the onset of CHF. 1170 5. DYNAMIC SYMPTOM EXPANSION In this
section, we address the challenges in computing symptom expansion
when the underlying symptom graph is changing. We first present our
algorithm, and then analyze its accuracy as well as the effic
than others, we further normalize a symptom matrix G constructed
using a method described above through the following G = GD1
where D is a diagonal matrix with Dii = P j Nij . The resulting matrix G
will be Markovian, namely the column sums to 1. In this
5% and raises HDL-cholesterol by approximately 5%. Ezetimibe is
currently licensed for use in combination with a statin in patients who
fail to reach desired lipid profiles or as monotherapy in patients
intolerant to a statin. Thiazides block Na+ and Cl-
low rank approximation U and V, the updated core matrix , and the
updated ranking vector r for the query vector e. 1: Update U and V
(Update_LowRank() 2: Re-form or approximate G as: G = XY 3:
Update: U [U X]; V V Y 4: Update Core Matrix (Update_Core() 5:
that the exposure E causes the disease D even if > 1, or vice versa. In
fact, the exposure E may not even occur before the event D. Since we
got good estimates of P[D|E] and P[D|E] bP[D|E] = n11 n1+ , bP[D|E]
= n21 n2+ , the relative risk can be estimated
given patient. The distance between patients can be defined based on
the similarity of the underlying symptom graphs. We can aggregate
individual patients symptom graphs into a population-level symptom
graph. A symptom graph G is represented as G = cfw_V,
perspective of symptom analysis and mining in the sense that it
contains essential and sufficient information about symptoms and their
relations required by many different mining applications. Below, we first
present the overall process of building sympto
Precision (AP), Precision at 50 (P@50), and Recall at N. Intuitively
precision at 50 tells us how many of the top-50 symptoms generated by
Update-RWR, were found in the gold standard. Recall at N gives the
percentage of gold standard symptoms that were re
are nausea, vomiting, diarrhoea, appetite and weight loss, sexual
dysfunction and deranged liver function tests. Similarly, the common
side effects of fluoxetine are :anxiety or nervousness; decreased
appetite; diarrhoea; drowsiness; headache; increased s
adjacency matrix G, the query vector e and c. Output: The ranking
vector for the source node r. 1: Pre-Compute Stage (NB_LIN_Pre() 2: do
low-rank approximation for G = UV 3: pre-compute and store the core
matrix = (I cVU) 1 4: On-Line Query Stage (NB_LIN_
related works include dynamic PageRank [14, 17], Fast SimRank [10, 9],
etc. Our work can be regarded as adding to this line of work a new
application of RWR for finding related symptoms in graphs of patient
symptoms. Prediction of patient diseases based o
in Alg. 2 gives the exact matrix. Then, for the updated ranking vector
r, we have r = (1 c)(I cA) 1 e = (1 c)(I cU V ) 1 e = (1 c)(I +
cU V )e = (1 c)(e + cU Ve ) (4) Notice that the second to the
last step is due to the ShermanMorrison lemma [15]. This c
(where l is the rank of the low-rank approximation) to get all possible
relevance scores. This solution [20], called NB_Lin, is summarized in Alg.
1 for completeness, where it is divided into two stages: NB_LIN_Pre()
and NB_LIN_OQ(). In NB_LIN_Pre() (step
been applied or adapted to the medical domain for recognizing various
entities such as diseases [22] and treatments [2]. We however, go
beyond symptom extraction to further construct symptom graphs and
study how to leverage such graphs to convert raw symp